wav2vec2-base-ks-ept4
This model is a fine-tuned version of facebook/wav2vec2-base on the superb dataset. It achieves the following results on the evaluation set:
- Loss: 1.5663
- Accuracy: 0.6209
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: 0.003
- train_batch_size: 256
- eval_batch_size: 256
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5133 | 1.0 | 50 | 1.5663 | 0.6209 |
| 1.4819 | 2.0 | 100 | 1.5675 | 0.6169 |
| 1.4082 | 3.0 | 150 | 1.5372 | 0.5802 |
| 1.3536 | 4.0 | 200 | 1.6716 | 0.5338 |
| 1.296 | 5.0 | 250 | 1.7601 | 0.5399 |
| 1.3053 | 6.0 | 300 | 1.6778 | 0.5630 |
| 1.2734 | 7.0 | 350 | 1.6554 | 0.5734 |
| 1.2837 | 8.0 | 400 | 1.7338 | 0.5741 |
| 1.2682 | 9.0 | 450 | 1.7313 | 0.5774 |
| 1.2776 | 10.0 | 500 | 1.7083 | 0.5791 |
Framework versions
- Transformers 4.22.0.dev0
- Pytorch 1.11.0+cu115
- Datasets 2.4.0
- Tokenizers 0.12.1
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