---
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: nllb-200-distilled-600M-finetuned-py2cpp
  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-finetuned-py2cpp

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1142
- Bleu: 58.3679
- Gen Len: 74.4727

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------:|
| No log        | 0.99  | 33   | 3.5500          | 28.0752 | 98.4545  |
| No log        | 2.0   | 67   | 2.6889          | 28.4762 | 97.7273  |
| No log        | 2.99  | 100  | 2.1016          | 13.9425 | 131.9636 |
| No log        | 4.0   | 134  | 1.6955          | 20.9551 | 114.3091 |
| No log        | 4.99  | 167  | 1.4578          | 44.5358 | 83.4     |
| No log        | 6.0   | 201  | 1.2986          | 53.9615 | 75.0545  |
| No log        | 6.99  | 234  | 1.2113          | 56.6086 | 77.4182  |
| No log        | 8.0   | 268  | 1.1550          | 57.2346 | 73.8364  |
| No log        | 8.99  | 301  | 1.1222          | 58.1529 | 74.2     |
| No log        | 9.85  | 330  | 1.1142          | 58.3679 | 74.4727  |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.13.3