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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_34 |
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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_34 |
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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: 0.6615 |
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- Rouge1: 0.9649 |
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- Rouge2: 0.8639 |
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- Rougel: 0.9148 |
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- Rougelsum: 0.916 |
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- Gen Len: 4.7917 |
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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 | 2.2768 | 0.4083 | 0.2813 | 0.3855 | 0.3853 | 17.3333 | |
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| No log | 2.0 | 24 | 1.7504 | 0.4318 | 0.2948 | 0.3978 | 0.3966 | 16.6042 | |
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| No log | 3.0 | 36 | 1.2490 | 0.4721 | 0.3506 | 0.4443 | 0.4447 | 15.3542 | |
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| No log | 4.0 | 48 | 0.9124 | 0.7673 | 0.6558 | 0.7251 | 0.7253 | 9.0833 | |
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| No log | 5.0 | 60 | 0.7653 | 0.9289 | 0.8292 | 0.8817 | 0.8823 | 5.7292 | |
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| No log | 6.0 | 72 | 0.7176 | 0.9649 | 0.8639 | 0.9148 | 0.916 | 4.7917 | |
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| No log | 7.0 | 84 | 0.6921 | 0.9649 | 0.8639 | 0.9148 | 0.916 | 4.7917 | |
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| No log | 8.0 | 96 | 0.6765 | 0.9649 | 0.8639 | 0.9148 | 0.916 | 4.7917 | |
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| No log | 9.0 | 108 | 0.6655 | 0.9649 | 0.8639 | 0.9148 | 0.916 | 4.7917 | |
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| No log | 10.0 | 120 | 0.6615 | 0.9649 | 0.8639 | 0.9148 | 0.916 | 4.7917 | |
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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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