speecht5_Kobe_finetune
This model is a fine-tuned version of blackbook-lab/speecht5_Kobe_finetune on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6849
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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8442 | 0.3704 | 10 | 0.7189 |
| 0.7748 | 0.7407 | 20 | 0.7182 |
| 0.7356 | 1.1111 | 30 | 0.7198 |
| 0.8104 | 1.4815 | 40 | 0.7147 |
| 1.5772 | 1.8519 | 50 | 0.7209 |
| 0.6864 | 2.2222 | 60 | 0.7140 |
| 0.9694 | 2.5926 | 70 | 0.7117 |
| 0.7178 | 2.9630 | 80 | 0.7107 |
| 0.6012 | 3.3333 | 90 | 0.7027 |
| 0.6419 | 3.7037 | 100 | 0.6981 |
| 0.8538 | 4.0741 | 110 | 0.6981 |
| 0.7592 | 4.4444 | 120 | 0.6877 |
| 0.6722 | 4.8148 | 130 | 0.6849 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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