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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-small |
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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: tidy-tab-model-t5-small |
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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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# tidy-tab-model-t5-small |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9997 |
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- Rouge1: 0.7404 |
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- Rouge2: 0.6249 |
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- Rougel: 0.7403 |
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- Rougelsum: 0.7413 |
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- Gen Len: 6.9017 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 1000 |
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- num_epochs: 32 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 2.3461 | 3.7879 | 500 | 1.0711 | 0.7407 | 0.6192 | 0.736 | 0.7374 | 7.188 | |
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| 1.0075 | 7.5758 | 1000 | 0.9645 | 0.7313 | 0.6071 | 0.7304 | 0.7303 | 6.9274 | |
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| 0.7921 | 11.3636 | 1500 | 0.9563 | 0.7306 | 0.6079 | 0.7323 | 0.7325 | 6.7863 | |
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| 0.6587 | 15.1515 | 2000 | 0.9697 | 0.7382 | 0.6142 | 0.739 | 0.7397 | 6.8675 | |
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| 0.5579 | 18.9394 | 2500 | 0.9905 | 0.7388 | 0.6203 | 0.7378 | 0.7395 | 6.8718 | |
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| 0.4984 | 22.7273 | 3000 | 0.9997 | 0.7404 | 0.6249 | 0.7403 | 0.7413 | 6.9017 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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