whisper-small-hi-en-ru-lang-id
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: 4.4504
- Accuracy: 0.5096
- F1: 0.4801
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0001 | 1.5936 | 500 | 4.3275 | 0.4994 | 0.4399 |
| 0.0 | 3.1873 | 1000 | 4.4504 | 0.5096 | 0.4801 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.2.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small