---
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: 2.6372
- Bleu: 6.3802
- Gen Len: 47.071

## 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: 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 |
|:-------------:|:------:|:-----:|:---------------:|:------:|:-------:|
| 2.1365        | 0.3476 | 1000  | 2.7681          | 2.9925 | 52.131  |
| 1.4326        | 0.6952 | 2000  | 2.5934          | 4.1353 | 45.036  |
| 1.2369        | 1.0428 | 3000  | 2.5647          | 5.0215 | 49.007  |
| 1.0832        | 1.3903 | 4000  | 2.5558          | 5.0661 | 48.543  |
| 1.036         | 1.7379 | 5000  | 2.5203          | 5.4399 | 47.738  |
| 0.9671        | 2.0855 | 6000  | 2.5657          | 5.8593 | 49.639  |
| 0.8711        | 2.4331 | 7000  | 2.5162          | 5.6784 | 47.706  |
| 0.8561        | 2.7807 | 8000  | 2.5742          | 5.9194 | 47.395  |
| 0.8103        | 3.1283 | 9000  | 2.6108          | 6.3266 | 47.508  |
| 0.7534        | 3.4758 | 10000 | 2.6139          | 6.22   | 48.42   |
| 0.747         | 3.8234 | 11000 | 2.6008          | 6.3408 | 46.571  |
| 0.7123        | 4.1710 | 12000 | 2.6372          | 6.3802 | 47.071  |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0