---
license: mit
tags:
- generated_from_trainer
datasets:
- iva_mt_wslot
metrics:
- bleu
model-index:
- name: iva_mt_wslot-m2m100_418M-en-pt
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: iva_mt_wslot
      type: iva_mt_wslot
      config: en-pt
      split: validation
      args: en-pt
    metrics:
    - name: Bleu
      type: bleu
      value: 67.0512
---

<!-- 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. -->

# iva_mt_wslot-m2m100_418M-en-pt

This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the iva_mt_wslot dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0119
- Bleu: 67.0512
- Gen Len: 20.3665

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.016         | 1.0   | 1842  | 0.0132          | 62.2701 | 20.1343 |
| 0.0103        | 2.0   | 3684  | 0.0117          | 65.7139 | 20.2191 |
| 0.0076        | 3.0   | 5526  | 0.0116          | 65.578  | 20.0926 |
| 0.0059        | 4.0   | 7368  | 0.0115          | 66.3728 | 20.4514 |
| 0.0043        | 5.0   | 9210  | 0.0117          | 65.8861 | 20.3781 |
| 0.0033        | 6.0   | 11052 | 0.0117          | 66.6496 | 20.4383 |
| 0.0026        | 7.0   | 12894 | 0.0119          | 67.0512 | 20.3665 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3