---
library_name: transformers
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart-large-50-finetuned-en-to-ba
  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. -->

# mbart-large-50-finetuned-en-to-ba

This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8138
- Bleu: 6.0837
- Gen Len: 46.235

## 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: 16
- eval_batch_size: 16
- seed: 0
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:------:|:-------:|
| 1.9435        | 0.6949 | 1000  | 2.6296          | 3.6886 | 47.431  |
| 1.2417        | 1.3899 | 2000  | 2.5577          | 4.294  | 52.199  |
| 1.0716        | 2.0848 | 3000  | 2.5397          | 5.2872 | 50.81   |
| 0.9341        | 2.7797 | 4000  | 2.5230          | 5.6413 | 46.144  |
| 0.843         | 3.4746 | 5000  | 2.5927          | 5.891  | 47.693  |
| 0.7785        | 4.1696 | 6000  | 2.6120          | 6.477  | 45.289  |
| 0.7117        | 4.8645 | 7000  | 2.6530          | 6.1367 | 45.901  |
| 0.6505        | 5.5594 | 8000  | 2.7041          | 6.0327 | 46.667  |
| 0.6209        | 6.2543 | 9000  | 2.7524          | 6.4298 | 46.083  |
| 0.5857        | 6.9493 | 10000 | 2.7564          | 6.2065 | 47.203  |
| 0.5484        | 7.6442 | 11000 | 2.7948          | 6.5806 | 46.407  |
| 0.5317        | 8.3391 | 12000 | 2.8138          | 6.0837 | 46.235  |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3