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---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: billsum_236_t5-base
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. -->
# billsum_236_t5-base
This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1143
- Rouge1: 0.1513
- Rouge2: 0.0546
- Rougel: 0.1244
- Rougelsum: 0.1245
- Gen Len: 18.979
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.2695 | 1.69 | 500 | 2.1398 | 0.157 | 0.0611 | 0.1279 | 0.1279 | 19.0 |
| 1.1033 | 3.38 | 1000 | 2.1182 | 0.1582 | 0.0629 | 0.1296 | 0.1297 | 18.9984 |
| 1.1178 | 5.07 | 1500 | 2.1133 | 0.1551 | 0.0594 | 0.1275 | 0.1277 | 18.979 |
| 1.0399 | 6.75 | 2000 | 2.1171 | 0.1538 | 0.058 | 0.1266 | 0.1266 | 18.9887 |
| 1.0364 | 8.44 | 2500 | 2.1143 | 0.1513 | 0.0546 | 0.1244 | 0.1245 | 18.979 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
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