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# id_ravdess_mel_spec_Vit_vit-tiny-patch16-224_2

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: 0.8514
- Accuracy: 0.7870

## 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: 43
- 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    | 3.4190          | 0.0324   |
| 3.577         | 2.0   | 16   | 3.1245          | 0.0972   |
| 3.124         | 3.0   | 24   | 2.9168          | 0.1806   |
| 2.7828        | 4.0   | 32   | 2.5031          | 0.2454   |
| 2.1565        | 5.0   | 40   | 2.0137          | 0.3796   |
| 2.1565        | 6.0   | 48   | 1.6643          | 0.5463   |
| 1.4039        | 7.0   | 56   | 1.4283          | 0.5880   |
| 0.8467        | 8.0   | 64   | 1.2302          | 0.6620   |
| 0.471         | 9.0   | 72   | 1.1420          | 0.6574   |
| 0.245         | 10.0  | 80   | 1.0551          | 0.7130   |
| 0.245         | 11.0  | 88   | 1.0008          | 0.7361   |
| 0.1111        | 12.0  | 96   | 0.9660          | 0.75     |
| 0.0515        | 13.0  | 104  | 0.9158          | 0.7407   |
| 0.0227        | 14.0  | 112  | 0.9132          | 0.7407   |
| 0.0106        | 15.0  | 120  | 0.8355          | 0.7685   |
| 0.0106        | 16.0  | 128  | 0.8486          | 0.7639   |
| 0.0042        | 17.0  | 136  | 0.8263          | 0.7778   |
| 0.0021        | 18.0  | 144  | 0.8304          | 0.7731   |
| 0.0013        | 19.0  | 152  | 0.8260          | 0.7824   |
| 0.0009        | 20.0  | 160  | 0.8407          | 0.7731   |
| 0.0009        | 21.0  | 168  | 0.8337          | 0.7824   |
| 0.0008        | 22.0  | 176  | 0.8311          | 0.7824   |
| 0.0006        | 23.0  | 184  | 0.8370          | 0.7778   |
| 0.0006        | 24.0  | 192  | 0.8371          | 0.7778   |
| 0.0005        | 25.0  | 200  | 0.8373          | 0.7870   |
| 0.0005        | 26.0  | 208  | 0.8399          | 0.7870   |
| 0.0005        | 27.0  | 216  | 0.8394          | 0.7870   |
| 0.0005        | 28.0  | 224  | 0.8412          | 0.7824   |
| 0.0004        | 29.0  | 232  | 0.8416          | 0.7870   |
| 0.0004        | 30.0  | 240  | 0.8431          | 0.7870   |
| 0.0004        | 31.0  | 248  | 0.8450          | 0.7824   |
| 0.0004        | 32.0  | 256  | 0.8430          | 0.7870   |
| 0.0004        | 33.0  | 264  | 0.8458          | 0.7824   |
| 0.0003        | 34.0  | 272  | 0.8466          | 0.7870   |
| 0.0003        | 35.0  | 280  | 0.8454          | 0.7870   |
| 0.0003        | 36.0  | 288  | 0.8468          | 0.7824   |
| 0.0003        | 37.0  | 296  | 0.8484          | 0.7870   |
| 0.0003        | 38.0  | 304  | 0.8484          | 0.7870   |
| 0.0003        | 39.0  | 312  | 0.8492          | 0.7824   |
| 0.0003        | 40.0  | 320  | 0.8498          | 0.7870   |
| 0.0003        | 41.0  | 328  | 0.8492          | 0.7870   |
| 0.0003        | 42.0  | 336  | 0.8491          | 0.7870   |
| 0.0003        | 43.0  | 344  | 0.8505          | 0.7870   |
| 0.0003        | 44.0  | 352  | 0.8509          | 0.7870   |
| 0.0003        | 45.0  | 360  | 0.8505          | 0.7870   |
| 0.0003        | 46.0  | 368  | 0.8509          | 0.7870   |
| 0.0003        | 47.0  | 376  | 0.8510          | 0.7870   |
| 0.0003        | 48.0  | 384  | 0.8511          | 0.7870   |
| 0.0003        | 49.0  | 392  | 0.8514          | 0.7870   |
| 0.0003        | 50.0  | 400  | 0.8514          | 0.7870   |


### 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