Whisper large LV - Felikss Kleins
This model is a fine-tuned version of AiLab-IMCS-UL/whisper-large-v3-lv-late-cv19 on the Recorded Voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.4380
- Wer: 25.9259
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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_hf 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.036 | 48.7805 | 1000 | 0.4135 | 19.7531 |
| 0.0196 | 97.5610 | 2000 | 0.4086 | 22.2222 |
| 0.0126 | 146.3415 | 3000 | 0.4710 | 23.4568 |
| 0.0117 | 195.1220 | 4000 | 0.4380 | 25.9259 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.3.1
- Datasets 3.1.0
- Tokenizers 0.20.2
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Base model
openai/whisper-large-v3