ser_model_adjusted_2023-03-03
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: 0.8997
- Accuracy: 0.7573
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7826 | 1.0 | 15 | 1.7119 | 0.3180 |
| 1.6174 | 2.0 | 30 | 1.5893 | 0.3808 |
| 1.5272 | 3.0 | 45 | 1.4628 | 0.4059 |
| 1.3355 | 4.0 | 60 | 1.3073 | 0.5230 |
| 1.2021 | 5.0 | 75 | 1.1725 | 0.5941 |
| 1.0797 | 6.0 | 90 | 1.0559 | 0.6904 |
| 0.9803 | 7.0 | 105 | 1.0222 | 0.7071 |
| 0.882 | 8.0 | 120 | 0.9297 | 0.7448 |
| 0.8505 | 9.0 | 135 | 0.8997 | 0.7573 |
| 0.7807 | 10.0 | 150 | 0.8801 | 0.7573 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.13.2
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