---
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
metrics:
- rouge
- sacrebleu
model-index:
- name: test_llm_nllb_colab_100_b2_e_12clrlinearreload
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# test_llm_nllb_colab_100_b2_e_12clrlinearreload

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: 0.5442
- Rouge1: 0.6187
- Rouge2: 0.3907
- Rougel: 0.573
- Sacrebleu: 23.8256

## 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: 2
- eval_batch_size: 2
- seed: 237
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.5035        | 1.0   | 2040  | 0.4985          | 0.5886 | 0.3527 | 0.5463 | 21.1436   |
| 0.4211        | 2.0   | 4080  | 0.4785          | 0.6043 | 0.3695 | 0.5589 | 22.5082   |
| 0.3277        | 3.0   | 6120  | 0.4776          | 0.6153 | 0.3792 | 0.5695 | 22.6802   |
| 0.2883        | 4.0   | 8160  | 0.4826          | 0.6142 | 0.3823 | 0.5695 | 23.3872   |
| 0.2641        | 5.0   | 10200 | 0.4900          | 0.6215 | 0.3881 | 0.5752 | 23.6105   |
| 0.2295        | 6.0   | 12240 | 0.5038          | 0.6166 | 0.3844 | 0.5709 | 23.3196   |
| 0.185         | 7.0   | 14280 | 0.5126          | 0.6155 | 0.3839 | 0.5704 | 23.4375   |
| 0.1777        | 8.0   | 16320 | 0.5230          | 0.6176 | 0.3867 | 0.5722 | 23.902    |
| 0.1445        | 9.0   | 18360 | 0.5305          | 0.621  | 0.3895 | 0.5735 | 23.7867   |
| 0.1354        | 10.0  | 20400 | 0.5373          | 0.6138 | 0.3825 | 0.5681 | 23.5844   |
| 0.1167        | 11.0  | 22440 | 0.5407          | 0.6173 | 0.3886 | 0.573  | 23.8997   |
| 0.1115        | 12.0  | 24480 | 0.5442          | 0.6187 | 0.3907 | 0.573  | 23.8256   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1