---
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: LMPT_project
  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. -->

# LMPT_project

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: 1.7558
- Bleu: 12.2835
- Gen Len: 44.0

## 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: 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 13   | 1.9988          | 0.6722  | 37.35   |
| No log        | 2.0   | 26   | 1.8930          | 0.7123  | 37.55   |
| No log        | 3.0   | 39   | 1.8316          | 12.8352 | 36.55   |
| No log        | 4.0   | 52   | 1.7920          | 17.2952 | 36.3    |
| No log        | 5.0   | 65   | 1.7743          | 16.9058 | 36.8    |
| No log        | 6.0   | 78   | 1.7652          | 17.4576 | 36.15   |
| No log        | 7.0   | 91   | 1.7601          | 11.2528 | 44.4    |
| No log        | 8.0   | 104  | 1.7578          | 12.2835 | 44.0    |
| No log        | 9.0   | 117  | 1.7556          | 12.2835 | 44.0    |
| No log        | 10.0  | 130  | 1.7558          | 12.2835 | 44.0    |


### Framework versions

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