---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: nllb_complete
  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_complete

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: 1.8285
- Bleu: 17.1412
- Gen Len: 17.896

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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
- lr_scheduler_warmup_steps: 5000
- num_epochs: 24.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step   | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-------:|:------:|:---------------:|:-------:|:-------:|
| 2.1296        | 1.4834  | 10000  | 2.0709          | 9.9056  | 20.1323 |
| 2.0253        | 2.9668  | 20000  | 1.9697          | 11.7423 | 19.27   |
| 1.8771        | 4.4503  | 30000  | 1.9199          | 13.3983 | 18.9643 |
| 1.7891        | 5.9338  | 40000  | 1.8851          | 14.1016 | 18.3833 |
| 1.7159        | 7.4173  | 50000  | 1.8680          | 14.8584 | 18.2797 |
| 1.6594        | 8.9007  | 60000  | 1.8473          | 15.8809 | 18.3863 |
| 1.6609        | 10.3842 | 70000  | 1.8406          | 15.8588 | 18.159  |
| 1.6358        | 11.8676 | 80000  | 1.8319          | 16.4395 | 18.4773 |
| 1.5623        | 13.3511 | 90000  | 1.8298          | 16.8956 | 18.3217 |
| 1.5534        | 14.8345 | 100000 | 1.8218          | 16.8725 | 18.5327 |
| 1.498         | 16.3180 | 110000 | 1.8286          | 16.6418 | 17.9697 |
| 1.4663        | 17.8014 | 120000 | 1.8252          | 17.2847 | 17.9357 |
| 1.4309        | 19.2849 | 130000 | 1.8299          | 17.027  | 17.7263 |
| 1.4398        | 20.7684 | 140000 | 1.8270          | 17.0189 | 18.1353 |
| 1.4534        | 22.2519 | 150000 | 1.8292          | 17.04   | 17.9637 |
| 1.4441        | 23.7353 | 160000 | 1.8285          | 17.1412 | 17.896  |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1