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wav2vec2-base-random-stop-classification-5
This model is a fine-tuned version of on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4239
- Accuracy: 0.8631
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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6916 | 0.99 | 18 | 0.6503 | 0.6362 |
| 0.6628 | 1.97 | 36 | 0.5354 | 0.7391 |
| 0.5922 | 2.96 | 54 | 0.4775 | 0.7786 |
| 0.5158 | 4.0 | 73 | 0.4559 | 0.8072 |
| 0.4733 | 4.99 | 91 | 0.4308 | 0.8188 |
| 0.4935 | 5.97 | 109 | 0.5186 | 0.7888 |
| 0.4512 | 6.96 | 127 | 0.4108 | 0.8358 |
| 0.4397 | 8.0 | 146 | 0.4692 | 0.8270 |
| 0.4037 | 8.99 | 164 | 0.4049 | 0.8304 |
| 0.4053 | 9.97 | 182 | 0.4054 | 0.8379 |
| 0.3774 | 10.96 | 200 | 0.4330 | 0.8379 |
| 0.3624 | 12.0 | 219 | 0.3800 | 0.8495 |
| 0.376 | 12.99 | 237 | 0.5123 | 0.8263 |
| 0.3908 | 13.97 | 255 | 0.4049 | 0.8386 |
| 0.3405 | 14.96 | 273 | 0.4200 | 0.8529 |
| 0.3542 | 16.0 | 292 | 0.4040 | 0.8569 |
| 0.3284 | 16.99 | 310 | 0.4578 | 0.8474 |
| 0.3094 | 17.97 | 328 | 0.4465 | 0.8522 |
| 0.2999 | 18.96 | 346 | 0.4126 | 0.8569 |
| 0.3059 | 20.0 | 365 | 0.4139 | 0.8529 |
| 0.2891 | 20.99 | 383 | 0.4101 | 0.8624 |
| 0.2968 | 21.97 | 401 | 0.4589 | 0.8501 |
| 0.2764 | 22.96 | 419 | 0.4263 | 0.8522 |
| 0.2841 | 24.0 | 438 | 0.4350 | 0.8597 |
| 0.2805 | 24.66 | 450 | 0.4239 | 0.8631 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
