---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
- wer
base_model: t5-small
model-index:
- name: genre-t5-small-60k
  results: []
---

# results_t5small

This model is a fine-tuned version of [t5-small](https://huggingface.co./t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0067
- Bleu: 95.7548
- Wer: 0.0246
- Gen Len: 62.3093

## Model description

TODO

## Intended uses & limitations

TODO

## Training and evaluation data

TODO

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 48
- eval_batch_size: 48
- 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 | Bleu    | Wer    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 0.0195        | 0.4   | 500  | 0.0153          | 93.2753 | 0.0427 | 62.7732 |
| 0.0128        | 0.8   | 1000 | 0.0109          | 94.7989 | 0.0312 | 62.7715 |
| 0.0121        | 1.2   | 1500 | 0.0094          | 95.0581 | 0.0295 | 62.266  |
| 0.0105        | 1.6   | 2000 | 0.0087          | 95.2607 | 0.0286 | 62.1432 |
| 0.009         | 2.0   | 2500 | 0.0083          | 95.3219 | 0.0274 | 62.2098 |
| 0.0096        | 2.4   | 3000 | 0.0077          | 95.4354 | 0.0268 | 62.2532 |
| 0.0071        | 2.8   | 3500 | 0.0075          | 95.5026 | 0.0261 | 62.3815 |
| 0.0072        | 3.2   | 4000 | 0.0073          | 95.5419 | 0.0259 | 62.5688 |
| 0.0074        | 3.6   | 4500 | 0.0071          | 95.6607 | 0.0254 | 62.7457 |
| 0.0076        | 4.0   | 5000 | 0.0068          | 95.6779 | 0.0251 | 62.892  |
| 0.0074        | 4.4   | 5500 | 0.0068          | 95.7313 | 0.0248 | 62.8282 |
| 0.0077        | 4.8   | 6000 | 0.0067          | 95.7548 | 0.0246 | 62.3093 |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.1