transformers safetensors whisper automatic-speech-recognition generated_from_trainer es en dataset:facebook/covost2 base_model:openai/whisper-large-v3 base_model:finetune:openai/whisper-large-v3 license:apache-2.0 model-index endpoints_compatible region:us
---
base_model: openai/whisper-large-v3
datasets:
- facebook/covost2
language:
- es
- en
library_name: transformers
license: apache-2.0
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: Whisper-large-v3-for-translation
  results:
  - task:
      type: translation
      name: Translation
    dataset:
      name: covost2
      type: facebook/covost2
      config: es_en
      split: None
      args: 'config: es, split: test, train'
    metrics:
    - type: bleu
      value: 41.85386637078158
      name: Bleu
---

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# Whisper-large-v3-for-translation

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the covost2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7779
- Bleu: 41.8539

## 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: 1e-05
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6494        | 1.0   | 4939 | 0.7779          | 41.8539 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
