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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: 1.0120 |
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- Rouge1: 0.7424 |
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- Rouge2: 0.6202 |
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- Rougel: 0.7365 |
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- Rougelsum: 0.7347 |
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- Gen Len: 7.0385 |
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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: 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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- num_epochs: 8 |
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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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| No log | 1.0 | 132 | 1.2896 | 0.6823 | 0.5884 | 0.6755 | 0.6759 | 8.9744 | |
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| No log | 2.0 | 264 | 1.1210 | 0.7277 | 0.6094 | 0.7187 | 0.7176 | 7.5342 | |
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| No log | 3.0 | 396 | 1.0676 | 0.7358 | 0.6136 | 0.7287 | 0.7273 | 7.3077 | |
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| 1.5149 | 4.0 | 528 | 1.0409 | 0.7462 | 0.6233 | 0.7386 | 0.7367 | 7.1368 | |
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| 1.5149 | 5.0 | 660 | 1.0277 | 0.7464 | 0.6233 | 0.7387 | 0.7367 | 7.1068 | |
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| 1.5149 | 6.0 | 792 | 1.0186 | 0.7463 | 0.6229 | 0.7383 | 0.7362 | 7.0769 | |
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| 1.5149 | 7.0 | 924 | 1.0135 | 0.7423 | 0.6202 | 0.7364 | 0.7346 | 7.0427 | |
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| 1.0709 | 8.0 | 1056 | 1.0120 | 0.7424 | 0.6202 | 0.7365 | 0.7347 | 7.0385 | |
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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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