|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- recall |
|
- precision |
|
model-index: |
|
- name: mixed_model_finetuned_ravdess |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yassmenyoussef55-arete-global/huggingface/runs/fbii58qd) |
|
# mixed_model_finetuned_ravdess |
|
|
|
This model is a fine-tuned version of [](https://huggingface.co/) 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 |
|
|
