---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/nllb-200-1.3B
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: nllb-200-1.3B-ft-eng-to-cym
  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-200-1.3B-ft-eng-to-cym

This model is a fine-tuned version of [facebook/nllb-200-1.3B](https://huggingface.co/facebook/nllb-200-1.3B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6294
- Bleu: 31.9664
- Gen Len: 56.0969

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 15000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
| 0.9749        | 0.0731 | 1000  | 0.8471          | 26.4405 | 64.7467 |
| 0.8876        | 0.1463 | 2000  | 0.7820          | 25.7663 | 72.4875 |
| 0.8296        | 0.2194 | 3000  | 0.7455          | 29.7194 | 64.5048 |
| 0.7953        | 0.2926 | 4000  | 0.7169          | 26.1134 | 62.5134 |
| 0.7682        | 0.3657 | 5000  | 0.6996          | 32.6703 | 55.0    |
| 0.7499        | 0.4389 | 6000  | 0.6835          | 30.9855 | 57.704  |
| 0.7238        | 0.5120 | 7000  | 0.6696          | 30.3129 | 54.3538 |
| 0.7184        | 0.5851 | 8000  | 0.6597          | 33.7707 | 53.5875 |
| 0.7171        | 0.6583 | 9000  | 0.6511          | 32.3995 | 53.0923 |
| 0.7062        | 0.7314 | 10000 | 0.6440          | 31.099  | 56.6207 |
| 0.691         | 0.8046 | 11000 | 0.6386          | 32.5796 | 55.578  |
| 0.6851        | 0.8777 | 12000 | 0.6343          | 32.4382 | 55.1046 |
| 0.6892        | 0.9508 | 13000 | 0.6317          | 31.7749 | 55.8827 |
| 0.6586        | 1.0240 | 14000 | 0.6304          | 31.799  | 56.5098 |
| 0.6659        | 1.0971 | 15000 | 0.6294          | 31.9664 | 56.0969 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0