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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: my_awesome_billsum_model_36 |
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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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# my_awesome_billsum_model_36 |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4601 |
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- Rouge1: 0.9721 |
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- Rouge2: 0.8819 |
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- Rougel: 0.9256 |
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- Rougelsum: 0.9271 |
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- Gen Len: 4.9167 |
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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: 10 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| No log | 1.0 | 12 | 1.9874 | 0.4145 | 0.2913 | 0.3883 | 0.3891 | 17.6042 | |
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| No log | 2.0 | 24 | 1.4300 | 0.4322 | 0.3091 | 0.4061 | 0.4068 | 17.0833 | |
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| No log | 3.0 | 36 | 0.9451 | 0.5076 | 0.3886 | 0.4814 | 0.48 | 14.75 | |
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| No log | 4.0 | 48 | 0.6345 | 0.8401 | 0.7297 | 0.7858 | 0.7884 | 7.625 | |
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| No log | 5.0 | 60 | 0.5226 | 0.9591 | 0.8586 | 0.8998 | 0.9042 | 5.125 | |
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| No log | 6.0 | 72 | 0.4907 | 0.9701 | 0.8736 | 0.9129 | 0.9167 | 4.8958 | |
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| No log | 7.0 | 84 | 0.4783 | 0.9701 | 0.8736 | 0.9129 | 0.9167 | 4.8958 | |
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| No log | 8.0 | 96 | 0.4697 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 | |
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| No log | 9.0 | 108 | 0.4627 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 | |
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| No log | 10.0 | 120 | 0.4601 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 | |
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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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