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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_more_tokens |
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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_more_tokens |
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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: 4.9713 |
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- Rouge: {'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782} |
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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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| 0.1018 | 1.0 | 1786 | 4.8212 | {'rouge1': 0.08214263320457528, 'rouge2': 0.07664435994602323, 'rougeL': 0.08165082402731275, 'rougeLsum': 0.08195136874817986} | {'exact_match': 0.0007692307692307692} | |
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| 0.0492 | 2.0 | 3572 | 4.9667 | {'rouge1': 0.14646008210615485, 'rouge2': 0.13764314957947393, 'rougeL': 0.14609763499439285, 'rougeLsum': 0.1462918679871027} | {'exact_match': 0.0} | |
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| 0.0495 | 3.0 | 5358 | 4.9713 | {'rouge1': 0.1482362658062074, 'rouge2': 0.13930032282405375, 'rougeL': 0.14788192707063608, 'rougeLsum': 0.14808345907939782} | {'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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