Training completed!
Browse files- README.md +15 -15
- config.json +1 -1
- pytorch_model.bin +1 -1
- tokenizer_config.json +4 -0
- training_args.bin +2 -2
README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-clinc
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 40 |
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| No log | 2.0 | 80 |
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| No log | 3.0 | 120 |
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| No log | 4.0 | 160 |
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| No log | 5.0 | 200 |
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| No log | 6.0 | 240 |
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| No log | 7.0 | 280 |
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### Framework versions
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---
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license: apache-2.0
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base_model: patnelt60/distilbert-base-uncased-finetuned-clinc
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9267741935483871
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-clinc
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This model is a fine-tuned version of [patnelt60/distilbert-base-uncased-finetuned-clinc](https://huggingface.co/patnelt60/distilbert-base-uncased-finetuned-clinc) on the clinc_oos dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1904
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- Accuracy: 0.9268
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 40 | 0.4572 | 0.8619 |
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| No log | 2.0 | 80 | 0.3775 | 0.8881 |
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| No log | 3.0 | 120 | 0.3184 | 0.9013 |
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| No log | 4.0 | 160 | 0.2753 | 0.9110 |
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| No log | 5.0 | 200 | 0.2441 | 0.9187 |
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| No log | 6.0 | 240 | 0.2224 | 0.9232 |
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| No log | 7.0 | 280 | 0.2073 | 0.9248 |
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| 0.3426 | 8.0 | 320 | 0.1982 | 0.9268 |
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| 0.3426 | 9.0 | 360 | 0.1923 | 0.9265 |
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| 0.3426 | 10.0 | 400 | 0.1904 | 0.9268 |
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### Framework versions
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config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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{
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"_name_or_path": "patnelt60/distilbert-base-uncased-finetuned-clinc",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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pytorch_model.bin
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tokenizer_config.json
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"unk_token": "[UNK]"
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}
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"max_length": 512,
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"stride": 0,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "DistilBertTokenizer",
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "[UNK]"
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}
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training_args.bin
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