metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-kashmiri
results: []
whisper-kashmiri
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: 0.6185
- Wer: 1.0
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6774 | 0.7692 | 10 | 0.7696 | 1.0 |
| 0.4691 | 1.5385 | 20 | 0.7671 | 1.0 |
| 0.2833 | 2.3077 | 30 | 0.8243 | 1.0 |
| 0.1373 | 3.0769 | 40 | 0.6162 | 1.0 |
| 0.0334 | 3.8462 | 50 | 0.6105 | 1.0 |
| 0.0225 | 4.6154 | 60 | 0.6185 | 1.0 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0