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---
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
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