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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- billsum |
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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-small-billsum |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: billsum |
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type: billsum |
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config: default |
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split: train[17000:] |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 24.0011 |
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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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# flan-t5-small-billsum |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the billsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5675 |
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- Rouge1: 24.0011 |
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- Rouge2: 18.8602 |
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- Rougel: 22.9037 |
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- Rougelsum: 23.1161 |
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- Gen Len: 19.0 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 5 |
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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 | 195 | 1.6773 | 22.8625 | 17.311 | 21.829 | 22.0089 | 19.0 | |
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| No log | 2.0 | 390 | 1.6134 | 23.6942 | 18.553 | 22.561 | 22.8895 | 19.0 | |
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| 1.9532 | 3.0 | 585 | 1.5882 | 23.8253 | 18.7086 | 22.6519 | 22.9745 | 19.0 | |
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| 1.9532 | 4.0 | 780 | 1.5739 | 24.0178 | 18.8429 | 22.9119 | 23.1471 | 19.0 | |
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| 1.9532 | 5.0 | 975 | 1.5675 | 24.0011 | 18.8602 | 22.9037 | 23.1161 | 19.0 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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