---
library_name: peft
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-1.3B
tags:
- generated_from_trainer
model-index:
- name: mn_nllb_1.3B_continue
  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. -->

# mn_nllb_1.3B_continue

This model is a fine-tuned version of [facebook/nllb-200-distilled-1.3B](https://huggingface.co/facebook/nllb-200-distilled-1.3B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.1680

## 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: 40
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 160
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.0421        | 0.32  | 20   | 7.1684          |
| 7.0297        | 0.64  | 40   | 7.1668          |
| 7.0254        | 0.96  | 60   | 7.1666          |
| 7.0207        | 1.272 | 80   | 7.1669          |
| 7.0429        | 1.592 | 100  | 7.1672          |
| 7.0276        | 1.912 | 120  | 7.1675          |
| 7.0199        | 2.224 | 140  | 7.1675          |
| 7.0254        | 2.544 | 160  | 7.1678          |
| 7.0379        | 2.864 | 180  | 7.1678          |
| 7.0454        | 3.176 | 200  | 7.1680          |
| 7.0415        | 3.496 | 220  | 7.1680          |
| 7.0466        | 3.816 | 240  | 7.1680          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0