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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-billsum
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-small-finetuned-billsum
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3166
- Rouge1: 58.6163
- Rouge2: 41.6107
- Rougel: 51.5177
- Rougelsum: 52.8486
- Gen Len: 62.2894
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.5373 | 0.4219 | 500 | 1.7306 | 44.8884 | 29.9047 | 38.8732 | 39.7098 | 49.8626 |
| 1.8175 | 0.8439 | 1000 | 1.5164 | 53.4663 | 36.8936 | 46.4756 | 47.6133 | 57.6953 |
| 1.6775 | 1.2658 | 1500 | 1.4401 | 55.9549 | 38.7969 | 48.6918 | 49.9216 | 60.5867 |
| 1.6 | 1.6878 | 2000 | 1.4016 | 56.8423 | 39.5972 | 49.5877 | 50.8088 | 61.5580 |
| 1.5717 | 2.1097 | 2500 | 1.3736 | 57.4282 | 40.2126 | 50.1498 | 51.3818 | 61.9033 |
| 1.5389 | 2.5316 | 3000 | 1.3570 | 57.6909 | 40.5046 | 50.4987 | 51.7769 | 62.0116 |
| 1.5183 | 2.9536 | 3500 | 1.3426 | 58.2372 | 41.1473 | 51.0517 | 52.3423 | 62.1297 |
| 1.499 | 3.3755 | 4000 | 1.3310 | 58.326 | 41.2564 | 51.1817 | 52.4513 | 62.2423 |
| 1.4845 | 3.7975 | 4500 | 1.3232 | 58.4925 | 41.5426 | 51.3865 | 52.6942 | 62.2276 |
| 1.4888 | 4.2194 | 5000 | 1.3203 | 58.5475 | 41.5865 | 51.4574 | 52.791 | 62.2710 |
| 1.48 | 4.6414 | 5500 | 1.3166 | 58.6163 | 41.6107 | 51.5177 | 52.8486 | 62.2894 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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