---
license: mit
base_model: facebook/m2m100_418M
tags:
- generated_from_trainer
model-index:
- name: output
  results: []
---

<!-- 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. -->

# output

This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1847

## 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: 5e-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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.7809        | 0.11  | 100  | 0.3955          |
| 0.379         | 0.23  | 200  | 0.2623          |
| 0.2876        | 0.34  | 300  | 0.2431          |
| 0.2733        | 0.46  | 400  | 0.2327          |
| 0.2885        | 0.57  | 500  | 0.2230          |
| 0.2414        | 0.69  | 600  | 0.2162          |
| 0.2347        | 0.8   | 700  | 0.2119          |
| 0.2509        | 0.91  | 800  | 0.2056          |
| 0.2237        | 1.03  | 900  | 0.2042          |
| 0.1759        | 1.14  | 1000 | 0.2009          |
| 0.1471        | 1.26  | 1100 | 0.1984          |
| 0.1759        | 1.37  | 1200 | 0.1959          |
| 0.1396        | 1.49  | 1300 | 0.1960          |
| 0.1656        | 1.6   | 1400 | 0.1936          |
| 0.163         | 1.71  | 1500 | 0.1898          |
| 0.1463        | 1.83  | 1600 | 0.1879          |
| 0.1662        | 1.94  | 1700 | 0.1858          |
| 0.1297        | 2.06  | 1800 | 0.1889          |
| 0.0841        | 2.17  | 1900 | 0.1886          |
| 0.1           | 2.29  | 2000 | 0.1880          |
| 0.0937        | 2.4   | 2100 | 0.1873          |
| 0.1023        | 2.51  | 2200 | 0.1862          |
| 0.0918        | 2.63  | 2300 | 0.1864          |
| 0.0981        | 2.74  | 2400 | 0.1863          |
| 0.0993        | 2.86  | 2500 | 0.1841          |
| 0.1086        | 2.97  | 2600 | 0.1834          |
| 0.083         | 3.09  | 2700 | 0.1869          |
| 0.07          | 3.2   | 2800 | 0.1873          |
| 0.0609        | 3.31  | 2900 | 0.1865          |
| 0.0637        | 3.43  | 3000 | 0.1861          |
| 0.078         | 3.54  | 3100 | 0.1862          |
| 0.0605        | 3.66  | 3200 | 0.1844          |
| 0.0606        | 3.77  | 3300 | 0.1845          |
| 0.0579        | 3.89  | 3400 | 0.1849          |
| 0.0687        | 4.0   | 3500 | 0.1847          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2