monika_asr
This model is a fine-tuned version of openai/whisper-large-v3 on the honzapucalek/monika_asr cs dataset. It achieves the following results on the evaluation set:
- Loss: 0.7834
- Wer: 0.2606
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: 8
- 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: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0001 | 45.4545 | 1000 | 0.6877 | 0.2625 |
0.0001 | 90.9091 | 2000 | 0.6910 | 0.2589 |
0.0 | 136.3636 | 3000 | 0.7108 | 0.2591 |
0.0 | 181.8182 | 4000 | 0.7377 | 0.2618 |
0.0 | 227.2727 | 5000 | 0.7669 | 0.2606 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.1.2+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0
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Base model
openai/whisper-large-v3Evaluation results
- Wer on honzapucalek/monika_asr cstest set self-reported0.261