test-model
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2455
- Accuracy: 0.9336
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 600
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9682 | 0.9639 | 60 | 0.8113 | 0.6177 |
| 0.7135 | 1.9277 | 120 | 0.6503 | 0.7425 |
| 0.585 | 2.8916 | 180 | 0.5173 | 0.8149 |
| 0.4603 | 3.8554 | 240 | 0.4556 | 0.8551 |
| 0.3855 | 4.8193 | 300 | 0.2616 | 0.9256 |
| 0.284 | 5.7831 | 360 | 0.3075 | 0.9235 |
| 0.2411 | 6.7470 | 420 | 0.2254 | 0.9376 |
| 0.1818 | 7.7108 | 480 | 0.2609 | 0.9356 |
| 0.1644 | 8.6747 | 540 | 0.2562 | 0.9336 |
| 0.1285 | 9.6386 | 600 | 0.2455 | 0.9336 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1