---
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: 0.1802

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.7737        | 0.11  | 100  | 0.4133          |
| 0.3772        | 0.23  | 200  | 0.2586          |
| 0.2884        | 0.34  | 300  | 0.2401          |
| 0.2732        | 0.46  | 400  | 0.2320          |
| 0.285         | 0.57  | 500  | 0.2212          |
| 0.2375        | 0.69  | 600  | 0.2143          |
| 0.232         | 0.8   | 700  | 0.2113          |
| 0.2468        | 0.91  | 800  | 0.2028          |
| 0.2222        | 1.03  | 900  | 0.1996          |
| 0.1715        | 1.14  | 1000 | 0.1971          |
| 0.1442        | 1.26  | 1100 | 0.1949          |
| 0.1726        | 1.37  | 1200 | 0.1936          |
| 0.1359        | 1.49  | 1300 | 0.1932          |
| 0.1613        | 1.6   | 1400 | 0.1912          |
| 0.1599        | 1.71  | 1500 | 0.1886          |
| 0.1431        | 1.83  | 1600 | 0.1856          |
| 0.1607        | 1.94  | 1700 | 0.1829          |
| 0.1269        | 2.06  | 1800 | 0.1867          |
| 0.0838        | 2.17  | 1900 | 0.1837          |
| 0.0982        | 2.29  | 2000 | 0.1850          |
| 0.0936        | 2.4   | 2100 | 0.1831          |
| 0.1009        | 2.51  | 2200 | 0.1832          |
| 0.0889        | 2.63  | 2300 | 0.1824          |
| 0.0956        | 2.74  | 2400 | 0.1813          |
| 0.0967        | 2.86  | 2500 | 0.1807          |
| 0.1075        | 2.97  | 2600 | 0.1802          |


### Framework versions

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