Bakobiibizo
commited on
Commit
•
e302db6
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Parent(s):
57241f6
Upload folder using huggingface_hub
Browse files- README.md +6 -0
- config copy.json +22 -0
- config.json +21 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- train_log.txt +281 -0
- training_args copy.json +132 -0
- training_args.bin +3 -0
- training_args.json +38 -0
- vocab.txt +0 -0
README.md
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## TextAttack Model Card
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This `lstm` model was fine-tuned using TextAttackand the *yelp_polarity* dataset loaded using the huggingface library. The model was fine-tuned for 50 epochs with a batch size of 8, a maximum sequence length of 128, and an initial learning rate of 1e-05.
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Since this was a classification task, the model was trained with a cross-entropy loss function. The best score the model achieved on this task was 0.9174473684210527, as measured by the eval set accuracy, found after 28 epochs.
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For more information on the source repo, check out [TextAttack on Github](https://github.com/QData/TextAttack).
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config copy.json
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{
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"architectures": [
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"BertForSequenceClassification"
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],
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"model_name": "my_model",
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"attention_probs_dropout_prob": 0.1,
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"finetuning_task": "yelp_polarity",
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"type_vocab_size": 2,
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"vocab_size": 30522
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}
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config.json
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{
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"finetuning_task": "yelp_polarity",
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"type_vocab_size": 2,
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"vocab_size": 30522
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c70002c363b84cb50fc02d63e9ebbc2bca966638b2958446c5a51094c7348c2e
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size 320670479
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer_config.json
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{"do_lower_case": true, "model_max_length": 512}
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train_log.txt
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Writing logs to ./outputs/2024-03-22-01-16-17-693140/train_log.txt.
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Wrote original training args to ./outputs/2024-03-22-01-16-17-693140/training_args.json.
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***** Running training *****
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Num examples = 560000
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Num epochs = 50
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Num clean epochs = 50
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Instantaneous batch size per device = 8
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Total train batch size (w. parallel, distributed & accumulation) = 8
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Gradient accumulation steps = 1
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Total optimization steps = 3500000
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==========================================================
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Epoch 1
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Running clean epoch 1/50
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Train accuracy: 81.85%
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Eval accuracy: 88.42%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 2
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Running clean epoch 2/50
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Train accuracy: 88.95%
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Eval accuracy: 88.87%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 3
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Running clean epoch 3/50
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Train accuracy: 89.65%
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Eval accuracy: 89.58%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 4
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Running clean epoch 4/50
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Train accuracy: 90.02%
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Eval accuracy: 89.53%
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==========================================================
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Epoch 5
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Running clean epoch 5/50
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Train accuracy: 90.22%
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Eval accuracy: 89.73%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 6
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Running clean epoch 6/50
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Train accuracy: 90.43%
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Eval accuracy: 89.60%
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==========================================================
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Epoch 7
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Running clean epoch 7/50
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Train accuracy: 90.64%
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Eval accuracy: 89.83%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 8
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Running clean epoch 8/50
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Train accuracy: 90.79%
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Eval accuracy: 90.04%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 9
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Running clean epoch 9/50
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Train accuracy: 90.97%
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Eval accuracy: 90.22%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 10
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Running clean epoch 10/50
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Train accuracy: 91.16%
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Eval accuracy: 90.33%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 11
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Running clean epoch 11/50
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Train accuracy: 91.37%
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Eval accuracy: 90.50%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 12
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Running clean epoch 12/50
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Train accuracy: 91.58%
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Eval accuracy: 90.42%
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==========================================================
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Epoch 13
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Running clean epoch 13/50
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Train accuracy: 91.81%
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Eval accuracy: 90.64%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 14
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Running clean epoch 14/50
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Train accuracy: 92.01%
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Eval accuracy: 90.71%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 15
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Running clean epoch 15/50
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Train accuracy: 92.23%
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Eval accuracy: 90.88%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 16
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Running clean epoch 16/50
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Train accuracy: 92.41%
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Eval accuracy: 90.95%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 17
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Running clean epoch 17/50
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Train accuracy: 92.59%
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Eval accuracy: 90.72%
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==========================================================
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Epoch 18
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Running clean epoch 18/50
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Train accuracy: 92.78%
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Eval accuracy: 91.12%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 19
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Running clean epoch 19/50
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Train accuracy: 92.97%
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Eval accuracy: 91.19%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 20
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Running clean epoch 20/50
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Train accuracy: 93.12%
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Eval accuracy: 91.43%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 21
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Running clean epoch 21/50
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Train accuracy: 93.28%
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Eval accuracy: 91.47%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 22
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Running clean epoch 22/50
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Train accuracy: 93.42%
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Eval accuracy: 91.52%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 23
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Running clean epoch 23/50
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Train accuracy: 93.54%
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Eval accuracy: 91.71%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 24
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Running clean epoch 24/50
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Train accuracy: 93.69%
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Eval accuracy: 91.61%
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==========================================================
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Epoch 25
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Running clean epoch 25/50
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Train accuracy: 93.86%
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Eval accuracy: 91.69%
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==========================================================
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Epoch 26
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Running clean epoch 26/50
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Train accuracy: 93.98%
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Eval accuracy: 91.63%
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==========================================================
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Epoch 27
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Running clean epoch 27/50
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Train accuracy: 94.12%
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Eval accuracy: 91.57%
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==========================================================
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Epoch 28
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Running clean epoch 28/50
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Train accuracy: 94.24%
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Eval accuracy: 91.74%
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Best score found. Saved model to ./outputs/2024-03-22-01-16-17-693140/best_model/
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==========================================================
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Epoch 29
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Running clean epoch 29/50
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Train accuracy: 94.37%
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Eval accuracy: 91.73%
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==========================================================
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Epoch 30
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Running clean epoch 30/50
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Train accuracy: 94.47%
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Eval accuracy: 91.45%
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==========================================================
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Epoch 31
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Running clean epoch 31/50
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Train accuracy: 94.62%
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Eval accuracy: 91.34%
|
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==========================================================
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Epoch 32
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Running clean epoch 32/50
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Train accuracy: 94.72%
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Eval accuracy: 91.58%
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==========================================================
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Epoch 33
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Running clean epoch 33/50
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Train accuracy: 94.86%
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Eval accuracy: 91.61%
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==========================================================
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Epoch 34
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Running clean epoch 34/50
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Train accuracy: 94.96%
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Eval accuracy: 91.70%
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==========================================================
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Epoch 35
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Running clean epoch 35/50
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Train accuracy: 95.06%
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Eval accuracy: 91.65%
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==========================================================
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Epoch 36
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Running clean epoch 36/50
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Train accuracy: 95.17%
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Eval accuracy: 91.71%
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==========================================================
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Epoch 37
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Running clean epoch 37/50
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Train accuracy: 95.28%
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Eval accuracy: 91.58%
|
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==========================================================
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Epoch 38
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Running clean epoch 38/50
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Train accuracy: 95.37%
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220 |
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Eval accuracy: 91.52%
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221 |
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==========================================================
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Epoch 39
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Running clean epoch 39/50
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224 |
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Train accuracy: 95.49%
|
225 |
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Eval accuracy: 91.10%
|
226 |
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==========================================================
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Epoch 40
|
228 |
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Running clean epoch 40/50
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Train accuracy: 95.58%
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230 |
+
Eval accuracy: 91.54%
|
231 |
+
==========================================================
|
232 |
+
Epoch 41
|
233 |
+
Running clean epoch 41/50
|
234 |
+
Train accuracy: 95.68%
|
235 |
+
Eval accuracy: 91.37%
|
236 |
+
==========================================================
|
237 |
+
Epoch 42
|
238 |
+
Running clean epoch 42/50
|
239 |
+
Train accuracy: 95.76%
|
240 |
+
Eval accuracy: 91.34%
|
241 |
+
==========================================================
|
242 |
+
Epoch 43
|
243 |
+
Running clean epoch 43/50
|
244 |
+
Train accuracy: 95.85%
|
245 |
+
Eval accuracy: 91.01%
|
246 |
+
==========================================================
|
247 |
+
Epoch 44
|
248 |
+
Running clean epoch 44/50
|
249 |
+
Train accuracy: 95.95%
|
250 |
+
Eval accuracy: 91.35%
|
251 |
+
==========================================================
|
252 |
+
Epoch 45
|
253 |
+
Running clean epoch 45/50
|
254 |
+
Train accuracy: 96.03%
|
255 |
+
Eval accuracy: 91.23%
|
256 |
+
==========================================================
|
257 |
+
Epoch 46
|
258 |
+
Running clean epoch 46/50
|
259 |
+
Train accuracy: 96.10%
|
260 |
+
Eval accuracy: 91.19%
|
261 |
+
==========================================================
|
262 |
+
Epoch 47
|
263 |
+
Running clean epoch 47/50
|
264 |
+
Train accuracy: 96.18%
|
265 |
+
Eval accuracy: 91.14%
|
266 |
+
==========================================================
|
267 |
+
Epoch 48
|
268 |
+
Running clean epoch 48/50
|
269 |
+
Train accuracy: 96.29%
|
270 |
+
Eval accuracy: 91.27%
|
271 |
+
==========================================================
|
272 |
+
Epoch 49
|
273 |
+
Running clean epoch 49/50
|
274 |
+
Train accuracy: 96.39%
|
275 |
+
Eval accuracy: 91.14%
|
276 |
+
==========================================================
|
277 |
+
Epoch 50
|
278 |
+
Running clean epoch 50/50
|
279 |
+
Train accuracy: 96.46%
|
280 |
+
Eval accuracy: 91.11%
|
281 |
+
Wrote README to ./outputs/2024-03-22-01-16-17-693140/README.md.
|
training_args copy.json
ADDED
@@ -0,0 +1,132 @@
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|
1 |
+
{
|
2 |
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"output_dir": "my_model",
|
3 |
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"overwrite_output_dir": false,
|
4 |
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|
5 |
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|
6 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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"learning_rate": 5e-05,
|
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|
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|
19 |
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"adam_beta2": 0.999,
|
20 |
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"adam_epsilon": 1e-08,
|
21 |
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|
22 |
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"num_train_epochs": 3.0,
|
23 |
+
"max_steps": -1,
|
24 |
+
"lr_scheduler_type": "linear",
|
25 |
+
"lr_scheduler_kwargs": {},
|
26 |
+
"warmup_ratio": 0.0,
|
27 |
+
"warmup_steps": 0,
|
28 |
+
"log_level": "passive",
|
29 |
+
"log_level_replica": "warning",
|
30 |
+
"log_on_each_node": true,
|
31 |
+
"logging_dir": "my_model/training_args.json/runs/Mar22_01-08-45_dsmtyh100xx0153",
|
32 |
+
"logging_strategy": "steps",
|
33 |
+
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|
34 |
+
"logging_steps": 500,
|
35 |
+
"logging_nan_inf_filter": true,
|
36 |
+
"save_strategy": "steps",
|
37 |
+
"save_steps": 500,
|
38 |
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"save_total_limit": null,
|
39 |
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|
40 |
+
"save_on_each_node": false,
|
41 |
+
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|
42 |
+
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|
43 |
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|
44 |
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|
45 |
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|
46 |
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|
47 |
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|
48 |
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|
49 |
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|
50 |
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|
51 |
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|
52 |
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|
53 |
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|
54 |
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|
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|
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|
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|
60 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
71 |
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|
72 |
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|
73 |
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|
74 |
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"fsdp": [],
|
75 |
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|
76 |
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"fsdp_config": {
|
77 |
+
"min_num_params": 0,
|
78 |
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|
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"xla_fsdp_v2": false,
|
80 |
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"xla_fsdp_grad_ckpt": false
|
81 |
+
},
|
82 |
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"fsdp_transformer_layer_cls_to_wrap": null,
|
83 |
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"accelerator_config": {
|
84 |
+
"split_batches": false,
|
85 |
+
"dispatch_batches": null,
|
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+
"even_batches": true,
|
87 |
+
"use_seedable_sampler": true
|
88 |
+
},
|
89 |
+
"deepspeed": null,
|
90 |
+
"label_smoothing_factor": 0.0,
|
91 |
+
"optim": "adamw_torch",
|
92 |
+
"optim_args": null,
|
93 |
+
"adafactor": false,
|
94 |
+
"group_by_length": false,
|
95 |
+
"length_column_name": "length",
|
96 |
+
"report_to": [],
|
97 |
+
"ddp_find_unused_parameters": null,
|
98 |
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"ddp_bucket_cap_mb": null,
|
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|
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"dataloader_pin_memory": true,
|
101 |
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"dataloader_persistent_workers": false,
|
102 |
+
"skip_memory_metrics": true,
|
103 |
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"use_legacy_prediction_loop": false,
|
104 |
+
"push_to_hub": false,
|
105 |
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"resume_from_checkpoint": null,
|
106 |
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"hub_model_id": null,
|
107 |
+
"hub_strategy": "every_save",
|
108 |
+
"hub_token": "<HUB_TOKEN>",
|
109 |
+
"hub_private_repo": false,
|
110 |
+
"hub_always_push": false,
|
111 |
+
"gradient_checkpointing": false,
|
112 |
+
"gradient_checkpointing_kwargs": null,
|
113 |
+
"include_inputs_for_metrics": false,
|
114 |
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"fp16_backend": "auto",
|
115 |
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"push_to_hub_model_id": null,
|
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"push_to_hub_organization": null,
|
117 |
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"push_to_hub_token": "<PUSH_TO_HUB_TOKEN>",
|
118 |
+
"mp_parameters": "",
|
119 |
+
"auto_find_batch_size": false,
|
120 |
+
"full_determinism": false,
|
121 |
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|
122 |
+
"ray_scope": "last",
|
123 |
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"ddp_timeout": 1800,
|
124 |
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|
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|
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|
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|
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|
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|
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|
131 |
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"neftune_noise_alpha": null
|
132 |
+
}
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d353037f945468aa95fe1a5029d9a81e6ddc9e0c380a50912a7731a06f54c0ee
|
3 |
+
size 203
|
training_args.json
ADDED
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
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|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"model_name_or_path": "lstm",
|
3 |
+
"attack": null,
|
4 |
+
"dataset": "yelp_polarity",
|
5 |
+
"task_type": "classification",
|
6 |
+
"model_max_length": null,
|
7 |
+
"model_num_labels": null,
|
8 |
+
"dataset_train_split": "train",
|
9 |
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"dataset_eval_split": "test",
|
10 |
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"filter_train_by_labels": null,
|
11 |
+
"filter_eval_by_labels": null,
|
12 |
+
"num_epochs": 50,
|
13 |
+
"num_clean_epochs": 1,
|
14 |
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"attack_epoch_interval": 1,
|
15 |
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"early_stopping_epochs": null,
|
16 |
+
"learning_rate": 1e-05,
|
17 |
+
"num_warmup_steps": 500,
|
18 |
+
"weight_decay": 0.01,
|
19 |
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"per_device_train_batch_size": 8,
|
20 |
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"per_device_eval_batch_size": 32,
|
21 |
+
"gradient_accumulation_steps": 1,
|
22 |
+
"random_seed": 786,
|
23 |
+
"parallel": false,
|
24 |
+
"load_best_model_at_end": false,
|
25 |
+
"alpha": 1.0,
|
26 |
+
"num_train_adv_examples": -1,
|
27 |
+
"query_budget_train": null,
|
28 |
+
"attack_num_workers_per_device": 1,
|
29 |
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"output_dir": "./outputs/2024-03-22-01-16-17-693140",
|
30 |
+
"checkpoint_interval_steps": null,
|
31 |
+
"checkpoint_interval_epochs": null,
|
32 |
+
"save_last": true,
|
33 |
+
"log_to_tb": false,
|
34 |
+
"tb_log_dir": null,
|
35 |
+
"log_to_wandb": false,
|
36 |
+
"wandb_project": "textattack",
|
37 |
+
"logging_interval_step": 1
|
38 |
+
}
|
vocab.txt
ADDED
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|
|