emotion_recognition
This model is a fine-tuned version of dima806/bird_sounds_classification on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7880
- Accuracy: 0.8249
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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7843 | 1.0 | 4899 | 0.9654 | 0.7514 |
| 0.6352 | 2.0 | 9798 | 0.9026 | 0.7955 |
| 0.0438 | 3.0 | 14697 | 0.8320 | 0.8037 |
| 0.443 | 4.0 | 19596 | 0.8014 | 0.8131 |
| 0.3585 | 5.0 | 24495 | 0.7880 | 0.8249 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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dima806/bird_sounds_classification