CV11_finetuning1
This model is a fine-tuned version of Roshana/Wav2Vec1_CV on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7162
- Wer: 0.3625
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5067 | 0.86 | 400 | 0.6193 | 0.4492 |
| 0.4448 | 1.72 | 800 | 0.6325 | 0.4384 |
| 0.3781 | 2.59 | 1200 | 0.6248 | 0.4197 |
| 0.3172 | 3.45 | 1600 | 0.6408 | 0.4343 |
| 0.2556 | 4.31 | 2000 | 0.6593 | 0.4230 |
| 0.2148 | 5.17 | 2400 | 0.6742 | 0.3987 |
| 0.1779 | 6.03 | 2800 | 0.6658 | 0.3929 |
| 0.1446 | 6.9 | 3200 | 0.6768 | 0.3846 |
| 0.1248 | 7.76 | 3600 | 0.6809 | 0.3804 |
| 0.108 | 8.62 | 4000 | 0.7214 | 0.3683 |
| 0.0938 | 9.48 | 4400 | 0.7162 | 0.3625 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1