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# id_ravdess_mel_spec_Vit_vit-tiny-patch16-224_1

This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8036
- Accuracy: 0.7917

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 8    | 3.5290          | 0.0231   |
| 3.7813        | 2.0   | 16   | 3.1577          | 0.0880   |
| 3.1834        | 3.0   | 24   | 2.9675          | 0.1435   |
| 2.8849        | 4.0   | 32   | 2.6636          | 0.2037   |
| 2.3044        | 5.0   | 40   | 2.2016          | 0.3565   |
| 2.3044        | 6.0   | 48   | 1.8205          | 0.4444   |
| 1.5789        | 7.0   | 56   | 1.5203          | 0.5417   |
| 1.0355        | 8.0   | 64   | 1.3309          | 0.6481   |
| 0.5941        | 9.0   | 72   | 1.2203          | 0.6528   |
| 0.3301        | 10.0  | 80   | 1.1015          | 0.6806   |
| 0.3301        | 11.0  | 88   | 1.0155          | 0.7176   |
| 0.1632        | 12.0  | 96   | 0.9678          | 0.7454   |
| 0.0791        | 13.0  | 104  | 0.9265          | 0.7454   |
| 0.0347        | 14.0  | 112  | 0.8884          | 0.75     |
| 0.0165        | 15.0  | 120  | 0.8745          | 0.7454   |
| 0.0165        | 16.0  | 128  | 0.8517          | 0.7824   |
| 0.007         | 17.0  | 136  | 0.8396          | 0.7593   |
| 0.0033        | 18.0  | 144  | 0.8265          | 0.7917   |
| 0.0019        | 19.0  | 152  | 0.8109          | 0.7685   |
| 0.0013        | 20.0  | 160  | 0.8015          | 0.7917   |
| 0.0013        | 21.0  | 168  | 0.8209          | 0.7917   |
| 0.001         | 22.0  | 176  | 0.7898          | 0.7917   |
| 0.0008        | 23.0  | 184  | 0.8016          | 0.7824   |
| 0.0007        | 24.0  | 192  | 0.8024          | 0.7824   |
| 0.0006        | 25.0  | 200  | 0.8014          | 0.7917   |
| 0.0006        | 26.0  | 208  | 0.7987          | 0.7824   |
| 0.0006        | 27.0  | 216  | 0.8025          | 0.7870   |
| 0.0006        | 28.0  | 224  | 0.8009          | 0.7824   |
| 0.0005        | 29.0  | 232  | 0.8001          | 0.7824   |
| 0.0005        | 30.0  | 240  | 0.8014          | 0.7870   |
| 0.0005        | 31.0  | 248  | 0.8025          | 0.7824   |
| 0.0005        | 32.0  | 256  | 0.8013          | 0.7824   |
| 0.0004        | 33.0  | 264  | 0.8026          | 0.7824   |
| 0.0004        | 34.0  | 272  | 0.8004          | 0.7824   |
| 0.0004        | 35.0  | 280  | 0.8027          | 0.7870   |
| 0.0004        | 36.0  | 288  | 0.8011          | 0.7824   |
| 0.0004        | 37.0  | 296  | 0.8036          | 0.7917   |
| 0.0004        | 38.0  | 304  | 0.8027          | 0.7824   |
| 0.0004        | 39.0  | 312  | 0.8028          | 0.7870   |
| 0.0004        | 40.0  | 320  | 0.8031          | 0.7824   |
| 0.0004        | 41.0  | 328  | 0.8037          | 0.7824   |
| 0.0004        | 42.0  | 336  | 0.8028          | 0.7870   |
| 0.0003        | 43.0  | 344  | 0.8027          | 0.7870   |
| 0.0003        | 44.0  | 352  | 0.8028          | 0.7824   |
| 0.0003        | 45.0  | 360  | 0.8034          | 0.7870   |
| 0.0003        | 46.0  | 368  | 0.8032          | 0.7870   |
| 0.0003        | 47.0  | 376  | 0.8031          | 0.7917   |
| 0.0003        | 48.0  | 384  | 0.8034          | 0.7870   |
| 0.0003        | 49.0  | 392  | 0.8037          | 0.7917   |
| 0.0003        | 50.0  | 400  | 0.8036          | 0.7917   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0

actor_01 actor_02 actor_11 actor_12 actor_13 actor_14 actor_15 actor_16 actor_17 actor_18 actor_19 actor_20 actor_03 actor_21 actor_22 actor_23 actor_24 actor_04 actor_05 actor_06 actor_07 actor_08 actor_09 actor_10