---
library_name: transformers
license: mit
base_model: NIRVLab/bartede
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: ViEde
  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. -->

# ViEde

This model is a fine-tuned version of [NIRVLab/bartede](https://huggingface.co/NIRVLab/bartede) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4809
- Bleu: 22.833
- Chrf++: 46.2491

## 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: 100
- eval_batch_size: 100
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Chrf++  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.273         | 1.0   | 2080 | 0.4809          | 22.833  | 46.2491 |
| 0.1331        | 2.0   | 4160 | 0.5284          | 24.6028 | 48.483  |
| 0.0964        | 3.0   | 6240 | 0.5543          | 25.6692 | 49.2306 |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2