---
license: mit
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: iva_mt_wslot-m2m100_418M-en-sv
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: iva_mt_wslot
      type: iva_mt_wslot
      config: en-sv
      split: validation
      args: en-sv
    metrics:
    - name: Bleu
      type: bleu
      value: 71.0808
datasets:
- cartesinus/iva_mt_wslot
language:
- en
- sv
---

<!-- 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-sv

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: 0.0107
- Bleu: 71.0808
- Gen Len: 19.7647

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.0151        | 1.0   | 1885  | 0.0120          | 67.2332 | 19.3956 |
| 0.0095        | 2.0   | 3770  | 0.0105          | 69.8147 | 19.675  |
| 0.0065        | 3.0   | 5655  | 0.0104          | 70.239  | 19.8404 |
| 0.0049        | 4.0   | 7540  | 0.0104          | 70.3673 | 19.7154 |
| 0.0038        | 5.0   | 9425  | 0.0105          | 70.1632 | 19.7743 |
| 0.0026        | 6.0   | 11310 | 0.0105          | 70.7959 | 19.7809 |
| 0.0021        | 7.0   | 13195 | 0.0107          | 71.0808 | 19.7647 |


### Framework versions

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