transformers tensorboard safetensors t5 text2text-generation generated_from_trainer dataset:opus_books base_model:t5-base license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- opus_books
metrics:
- bleu
model-index:
- name: opus_books_es_pt
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: opus_books
      type: opus_books
      config: es-pt
      split: train
      args: es-pt
    metrics:
    - name: Bleu
      type: bleu
      value: 1.2169
---

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# opus_books_es_pt

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the opus_books dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0763
- Bleu: 1.2169
- Gen Len: 18.5038

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 133  | 2.5227          | 0.5795 | 18.5789 |
| No log        | 2.0   | 266  | 2.3918          | 0.6703 | 18.5451 |
| No log        | 3.0   | 399  | 2.3166          | 0.8471 | 18.5301 |
| 2.6664        | 4.0   | 532  | 2.2665          | 0.8914 | 18.4737 |
| 2.6664        | 5.0   | 665  | 2.2319          | 0.928  | 18.4549 |
| 2.6664        | 6.0   | 798  | 2.2025          | 1.0067 | 18.5113 |
| 2.6664        | 7.0   | 931  | 2.1784          | 1.0162 | 18.515  |
| 2.2503        | 8.0   | 1064 | 2.1580          | 1.1102 | 18.5113 |
| 2.2503        | 9.0   | 1197 | 2.1420          | 1.0638 | 18.515  |
| 2.2503        | 10.0  | 1330 | 2.1257          | 1.1149 | 18.5113 |
| 2.2503        | 11.0  | 1463 | 2.1142          | 1.1334 | 18.4474 |
| 2.1172        | 12.0  | 1596 | 2.1091          | 1.1308 | 18.4925 |
| 2.1172        | 13.0  | 1729 | 2.0980          | 1.1655 | 18.5075 |
| 2.1172        | 14.0  | 1862 | 2.0950          | 1.1464 | 18.4925 |
| 2.1172        | 15.0  | 1995 | 2.0890          | 1.1383 | 18.5038 |
| 2.0185        | 16.0  | 2128 | 2.0833          | 1.1671 | 18.5    |
| 2.0185        | 17.0  | 2261 | 2.0806          | 1.1555 | 18.5038 |
| 2.0185        | 18.0  | 2394 | 2.0777          | 1.15   | 18.5113 |
| 1.9882        | 19.0  | 2527 | 2.0770          | 1.2252 | 18.5113 |
| 1.9882        | 20.0  | 2660 | 2.0763          | 1.2169 | 18.5038 |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
