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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-t5/t5-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: continue_pretrain_t5_base_10tokens |
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results: [] |
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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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# continue_pretrain_t5_base_10tokens |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.0015 |
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- Rouge: {'rouge1': 0.15180664921665177, 'rouge2': 0.14241763000023774, 'rougeL': 0.1513952140128575, 'rougeLsum': 0.1517189553463021} |
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- Exact Match: {'exact_match': 0.0} |
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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: 2e-05 |
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- train_batch_size: 14 |
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- eval_batch_size: 14 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 28 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge | Exact Match | |
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|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------:|:--------------------:| |
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| 0.1039 | 1.0 | 1786 | 4.8370 | {'rouge1': 0.08468086761955296, 'rouge2': 0.07928600729695852, 'rougeL': 0.08453698334268148, 'rougeLsum': 0.08473098923719942} | {'exact_match': 0.0} | |
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| 0.0503 | 2.0 | 3572 | 4.9960 | {'rouge1': 0.15080775818986453, 'rouge2': 0.1414201900527639, 'rougeL': 0.15034957154685738, 'rougeLsum': 0.1506605398259596} | {'exact_match': 0.0} | |
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| 0.0521 | 3.0 | 5358 | 5.0015 | {'rouge1': 0.15180664921665177, 'rouge2': 0.14241763000023774, 'rougeL': 0.1513952140128575, 'rougeLsum': 0.1517189553463021} | {'exact_match': 0.0} | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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