transformers tensorboard safetensors m2m_100 text2text-generation translation generated_from_trainer base_model:facebook/nllb-200-distilled-600M base_model:finetune:facebook/nllb-200-distilled-600M license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/nllb-200-distilled-600M
library_name: transformers
license: cc-by-nc-4.0
metrics:
- bleu
tags:
- translation
- generated_from_trainer
model-index:
- name: nllb-200-distilled-600M-mt-finetuned-zindi-dyu-to-fr
  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. -->

# nllb-200-distilled-600M-mt-finetuned-zindi-dyu-to-fr

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2584
- Bleu: 6.4075

## 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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu   |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.1707        | 0.1575 | 20   | 2.7356          | 4.8084 |
| 2.9074        | 0.3150 | 40   | 2.5883          | 5.0141 |
| 2.7168        | 0.4724 | 60   | 2.4902          | 5.5785 |
| 2.6912        | 0.6299 | 80   | 2.4154          | 5.7743 |
| 2.6062        | 0.7874 | 100  | 2.3742          | 6.0010 |
| 2.5794        | 0.9449 | 120  | 2.3480          | 6.1354 |
| 2.4634        | 1.1024 | 140  | 2.3314          | 5.9899 |
| 2.5055        | 1.2598 | 160  | 2.3167          | 6.1080 |
| 2.5062        | 1.4173 | 180  | 2.3032          | 6.3784 |
| 2.4771        | 1.5748 | 200  | 2.2944          | 6.4510 |
| 2.4284        | 1.7323 | 220  | 2.2854          | 6.2883 |
| 2.4423        | 1.8898 | 240  | 2.2783          | 6.5036 |
| 2.3202        | 2.0472 | 260  | 2.2730          | 6.4039 |
| 2.3855        | 2.2047 | 280  | 2.2701          | 6.2921 |
| 2.4292        | 2.3622 | 300  | 2.2658          | 6.3025 |
| 2.3678        | 2.5197 | 320  | 2.2626          | 6.2881 |
| 2.4158        | 2.6772 | 340  | 2.2600          | 6.3684 |
| 2.351         | 2.8346 | 360  | 2.2588          | 6.2852 |
| 2.3755        | 2.9921 | 380  | 2.2584          | 6.2819 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
