samuellimabraz
commited on
Commit
•
f16d96e
1
Parent(s):
f523ece
End of training
Browse files- README.md +97 -0
- adapter_config.json +29 -0
- adapter_model.safetensors +3 -0
- all_results.json +12 -0
- special_tokens_map.json +107 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +937 -0
- train_results.json +12 -0
- trainer_state.json +2400 -0
- training_args.bin +3 -0
README.md
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---
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base_model: google-t5/t5-base
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datasets:
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- Andyrasika/TweetSumm-tuned
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library_name: peft
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license: apache-2.0
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metrics:
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- rouge
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- f1
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- precision
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- recall
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tags:
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- generated_from_trainer
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model-index:
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- name: t5-base-qlora-finetune-tweetsumm-1724817707
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results:
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- task:
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type: summarization
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name: Summarization
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dataset:
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name: Andyrasika/TweetSumm-tuned
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type: Andyrasika/TweetSumm-tuned
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metrics:
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- type: rouge
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value: 0.4708
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name: Rouge1
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- type: f1
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value: 0.8942
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name: F1
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- type: precision
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value: 0.8941
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name: Precision
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- type: recall
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value: 0.8945
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name: Recall
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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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should probably proofread and complete it, then remove this comment. -->
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# t5-base-qlora-finetune-tweetsumm-1724817707
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the Andyrasika/TweetSumm-tuned dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7934
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- Rouge1: 0.4708
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- Rouge2: 0.2246
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- Rougel: 0.3984
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- Rougelsum: 0.4357
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- Gen Len: 49.4091
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- F1: 0.8942
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- Precision: 0.8941
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- Recall: 0.8945
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0005
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 2
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- num_epochs: 3
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:---------:|:------:|
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| 2.062 | 1.0 | 110 | 1.8472 | 0.4633 | 0.2177 | 0.3919 | 0.428 | 49.7273 | 0.8911 | 0.8897 | 0.8927 |
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| 1.7853 | 2.0 | 220 | 1.8120 | 0.4633 | 0.2203 | 0.3941 | 0.4285 | 49.4273 | 0.8953 | 0.8945 | 0.8963 |
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| 1.5952 | 3.0 | 330 | 1.7934 | 0.4708 | 0.2246 | 0.3984 | 0.4357 | 49.4091 | 0.8942 | 0.8941 | 0.8945 |
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### Framework versions
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- PEFT 0.12.1.dev0
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- Transformers 4.44.0
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- Pytorch 2.4.0
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "google-t5/t5-base",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q",
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"v"
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],
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"task_type": "SEQ_2_SEQ_LM",
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"use_dora": false,
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"use_rslora": true
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1d57bf549a5c134ffee8300f9e4ed5c32cf63baeff88092a8b2570e64babc6e0
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size 7098016
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all_results.json
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{
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"all_params": 153894144,
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"epoch": 3.0,
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"memory_footprint": 403239936,
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"total_flos": 2506179136462848.0,
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"train_loss": 1.8787952170227513,
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"train_runtime": 633.4063,
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"train_samples_per_second": 4.163,
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"train_steps_per_second": 0.521,
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"trainable_params": 1769472,
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"trainable_params_percent": 1.1497981365684713
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}
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special_tokens_map.json
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{
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"additional_special_tokens": [
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"unk_token": "<unk>"
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}
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spiece.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
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size 791656
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tokenizer.json
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tokenizer_config.json
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1 |
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train_results.json
ADDED
@@ -0,0 +1,12 @@
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{
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trainer_state.json
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@@ -0,0 +1,2400 @@
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