metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: mixed_model_finetuned_ravdess
results: []
mixed_model_finetuned_ravdess
This model is a fine-tuned version of on RAVDESS dataset. It achieves the following results on the evaluation set:
- Loss: 0.2728
- Accuracy: 0.9271
- F1: 0.9267
- Recall: 0.9271
- Precision: 0.9292
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 144
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 1.8272 | 1.0 | 36 | 1.3361 | 0.5312 | 0.4687 | 0.5312 | 0.5125 |
| 1.0357 | 2.0 | 72 | 0.7544 | 0.7674 | 0.7490 | 0.7674 | 0.8045 |
| 0.5699 | 3.0 | 108 | 0.3596 | 0.9097 | 0.9094 | 0.9097 | 0.9149 |
| 0.3445 | 4.0 | 144 | 0.2728 | 0.9271 | 0.9267 | 0.9271 | 0.9292 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1