my_awesome_torgo_model
This model is a fine-tuned version of facebook/wav2vec2-base on the Torgo dataset from Kaggle. It achieves the following results on the evaluation set:
- Loss: 0.3247
- Accuracy: 0.9025
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 |
|---|---|---|---|---|
| 0.6719 | 0.96 | 12 | 0.6555 | 0.6125 |
| 0.5695 | 2.0 | 25 | 0.7279 | 0.63 |
| 0.5342 | 2.96 | 37 | 0.5475 | 0.7875 |
| 0.4305 | 4.0 | 50 | 0.6443 | 0.7225 |
| 0.4174 | 4.96 | 62 | 0.6488 | 0.71 |
| 0.3563 | 6.0 | 75 | 0.3986 | 0.865 |
| 0.3502 | 6.96 | 87 | 0.3162 | 0.9 |
| 0.3036 | 8.0 | 100 | 0.3452 | 0.8925 |
| 0.2862 | 8.96 | 112 | 0.3452 | 0.895 |
| 0.2628 | 9.6 | 120 | 0.3247 | 0.9025 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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