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bambara-asr-v4
This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6734
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: 4
- total_train_batch_size: 32
- 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: 50
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9052 | 1.0 | 1708 | 0.9113 |
| 0.8135 | 2.0 | 3416 | 0.8085 |
| 0.762 | 3.0 | 5124 | 0.7595 |
| 0.728 | 4.0 | 6832 | 0.7322 |
| 0.6884 | 5.0 | 8540 | 0.7113 |
| 0.6784 | 6.0 | 10248 | 0.6970 |
| 0.6616 | 7.0 | 11956 | 0.6868 |
| 0.679 | 8.0 | 13664 | 0.6789 |
| 0.6574 | 9.0 | 15372 | 0.6754 |
| 0.6217 | 9.9946 | 17070 | 0.6734 |
Framework versions
- PEFT 0.14.1.dev0
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for sudoping01/bambara-asr-v4
Base model
openai/whisper-large-v2