---
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: 0.7738
- Bleu: 67.4647
- Gen Len: 75.9455

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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        | 1.0   | 67   | 2.6896          | 29.0389 | 96.5455 |
| No log        | 2.0   | 134  | 1.6534          | 30.4693 | 96.6727 |
| No log        | 3.0   | 201  | 1.2046          | 55.0467 | 76.7455 |
| No log        | 4.0   | 268  | 1.0048          | 59.5519 | 76.9091 |
| No log        | 5.0   | 335  | 0.9176          | 64.2229 | 75.5455 |
| No log        | 6.0   | 402  | 0.8610          | 65.8311 | 73.6909 |
| No log        | 7.0   | 469  | 0.8160          | 65.5771 | 76.4727 |
| 1.5731        | 8.0   | 536  | 0.7968          | 67.9558 | 74.7636 |
| 1.5731        | 9.0   | 603  | 0.7794          | 67.5994 | 75.8    |
| 1.5731        | 10.0  | 670  | 0.7738          | 67.4647 | 75.9455 |


### Framework versions

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