metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-no-specific-topic-v3
results: []
whisper-tiny-no-specific-topic-v3
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8726
- Wer: 40.7091
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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use 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: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4891 | 0.125 | 1000 | 0.7647 | 45.5818 |
| 0.4681 | 0.25 | 2000 | 0.7404 | 45.5727 |
| 0.2846 | 0.375 | 3000 | 0.7901 | 41.1909 |
| 0.3004 | 0.5 | 4000 | 0.8354 | 45.9455 |
| 0.2533 | 0.625 | 5000 | 0.8392 | 41.8182 |
| 0.2314 | 0.75 | 6000 | 0.8626 | 41.5 |
| 0.2622 | 0.875 | 7000 | 0.8690 | 43.5545 |
| 0.2165 | 1.0 | 8000 | 0.8726 | 40.7091 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0