metadata
library_name: transformers
license: mit
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-spanish
results: []
datasets:
- ciempiess/ciempiess_balance
- ciempiess/ciempiess_test
whisper-small-espaniol
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5077
- Wer: 12.9740
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2575 | 2.0 | 1000 | 0.3851 | 14.5929 |
| 0.0644 | 4.0 | 2000 | 0.4300 | 13.7753 |
| 0.0128 | 6.0 | 3000 | 0.4979 | 13.6955 |
| 0.0035 | 8.0 | 4000 | 0.5077 | 12.9740 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1