---
license: mit
tags:
- generated_from_trainer
datasets:
- iva_mt_wslot
metrics:
- bleu
model-index:
- name: iva_mt_wslot-m2m100_418M-zh-en
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: iva_mt_wslot
      type: iva_mt_wslot
      config: en-zh
      split: validation
      args: en-zh
    metrics:
    - name: Bleu
      type: bleu
      value: 67.9385
---

<!-- 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-zh-en

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: 0.0139
- Bleu: 67.9385
- Gen Len: 18.9988

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.016         | 1.0   | 2437  | 0.0138          | 62.077  | 18.6077 |
| 0.0114        | 2.0   | 4874  | 0.0126          | 64.3834 | 18.9019 |
| 0.0084        | 3.0   | 7311  | 0.0123          | 66.0012 | 18.9206 |
| 0.0067        | 4.0   | 9748  | 0.0123          | 66.7838 | 19.0018 |
| 0.005         | 5.0   | 12185 | 0.0124          | 66.9053 | 18.9527 |
| 0.0039        | 6.0   | 14622 | 0.0128          | 67.5252 | 18.9918 |
| 0.003         | 7.0   | 17059 | 0.0131          | 67.3664 | 18.9609 |
| 0.0025        | 8.0   | 19496 | 0.0135          | 67.792  | 19.0198 |
| 0.0019        | 9.0   | 21933 | 0.0137          | 67.7256 | 18.9591 |
| 0.0015        | 10.0  | 24370 | 0.0139          | 67.9385 | 18.9988 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.13.3