metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-hi
results: []
whisper-small-hi
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0011
- Wer: 0.0332
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0 | 5.7143 | 1000 | 0.0010 | 0.0332 |
| 0.0 | 11.4286 | 2000 | 0.0010 | 0.0498 |
| 0.0 | 17.1429 | 3000 | 0.0011 | 0.0332 |
| 0.0 | 22.8571 | 4000 | 0.0011 | 0.0332 |
| 0.0 | 28.5714 | 5000 | 0.0011 | 0.0332 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1