---
license: mit
tags:
- generated_from_trainer
datasets:
- cartesinus/iva_mt_wslot
metrics:
- bleu
model-index:
- name: iva_mt_wslot-m2m100_418M-en-de
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: iva_mt_wslot
      type: iva_mt_wslot
      config: en-de
      split: validation
      args: en-de
    metrics:
    - name: Bleu
      type: bleu
      value: 66.5548
language:
- en
- de
---

<!-- 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-de

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: 0.0126
- Bleu: 66.5548
- Gen Len: 20.6835

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.0183        | 1.0   | 1884  | 0.0144          | 63.5045 | 20.2994 |
| 0.0119        | 2.0   | 3768  | 0.0127          | 66.0473 | 20.5423 |
| 0.0083        | 3.0   | 5652  | 0.0123          | 65.5139 | 20.5409 |
| 0.0065        | 4.0   | 7536  | 0.0124          | 66.0731 | 20.6114 |
| 0.0048        | 5.0   | 9420  | 0.0122          | 66.2454 | 20.5906 |
| 0.0038        | 6.0   | 11304 | 0.0124          | 66.7412 | 20.6263 |
| 0.0031        | 7.0   | 13188 | 0.0126          | 66.5548 | 20.6835 |


### Framework versions

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