id_ravdess_mel_spec_Vit_swin-tiny-patch4-window7-224_2
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2989
- Accuracy: 0.8981
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 | 3.1629 | 0.0463 |
| 3.2006 | 2.0 | 16 | 3.0994 | 0.1343 |
| 3.1171 | 3.0 | 24 | 2.9243 | 0.25 |
| 2.8825 | 4.0 | 32 | 2.5593 | 0.3287 |
| 2.3542 | 5.0 | 40 | 2.0665 | 0.4907 |
| 2.3542 | 6.0 | 48 | 1.6166 | 0.5741 |
| 1.6626 | 7.0 | 56 | 1.2288 | 0.6852 |
| 1.1051 | 8.0 | 64 | 1.0197 | 0.7130 |
| 0.7312 | 9.0 | 72 | 0.8346 | 0.75 |
| 0.4713 | 10.0 | 80 | 0.7557 | 0.7593 |
| 0.4713 | 11.0 | 88 | 0.6095 | 0.8241 |
| 0.2823 | 12.0 | 96 | 0.5716 | 0.8056 |
| 0.1572 | 13.0 | 104 | 0.4956 | 0.8333 |
| 0.1104 | 14.0 | 112 | 0.4822 | 0.8380 |
| 0.0772 | 15.0 | 120 | 0.4910 | 0.8519 |
| 0.0772 | 16.0 | 128 | 0.4082 | 0.8935 |
| 0.0575 | 17.0 | 136 | 0.3986 | 0.875 |
| 0.0366 | 18.0 | 144 | 0.4707 | 0.8241 |
| 0.0287 | 19.0 | 152 | 0.4791 | 0.8426 |
| 0.0252 | 20.0 | 160 | 0.4041 | 0.8704 |
| 0.0252 | 21.0 | 168 | 0.4406 | 0.8519 |
| 0.036 | 22.0 | 176 | 0.3919 | 0.8796 |
| 0.0251 | 23.0 | 184 | 0.4180 | 0.8704 |
| 0.0176 | 24.0 | 192 | 0.3936 | 0.8657 |
| 0.0142 | 25.0 | 200 | 0.3191 | 0.8981 |
| 0.0142 | 26.0 | 208 | 0.3062 | 0.8889 |
| 0.0091 | 27.0 | 216 | 0.3444 | 0.8796 |
| 0.0135 | 28.0 | 224 | 0.4647 | 0.8519 |
| 0.0147 | 29.0 | 232 | 0.3634 | 0.875 |
| 0.0172 | 30.0 | 240 | 0.4332 | 0.875 |
| 0.0172 | 31.0 | 248 | 0.3612 | 0.8704 |
| 0.0111 | 32.0 | 256 | 0.3731 | 0.875 |
| 0.0076 | 33.0 | 264 | 0.4858 | 0.8657 |
| 0.0139 | 34.0 | 272 | 0.3653 | 0.8843 |
| 0.0063 | 35.0 | 280 | 0.4072 | 0.8704 |
| 0.0063 | 36.0 | 288 | 0.3097 | 0.8796 |
| 0.0073 | 37.0 | 296 | 0.3541 | 0.8704 |
| 0.0079 | 38.0 | 304 | 0.3692 | 0.8889 |
| 0.0064 | 39.0 | 312 | 0.3086 | 0.9074 |
| 0.0057 | 40.0 | 320 | 0.3198 | 0.8935 |
| 0.0057 | 41.0 | 328 | 0.3424 | 0.9028 |
| 0.0045 | 42.0 | 336 | 0.2878 | 0.9028 |
| 0.0038 | 43.0 | 344 | 0.2910 | 0.9074 |
| 0.0026 | 44.0 | 352 | 0.2817 | 0.8981 |
| 0.0051 | 45.0 | 360 | 0.2945 | 0.8796 |
| 0.0051 | 46.0 | 368 | 0.2729 | 0.9028 |
| 0.0036 | 47.0 | 376 | 0.2742 | 0.9028 |
| 0.006 | 48.0 | 384 | 0.3017 | 0.8981 |
| 0.0011 | 49.0 | 392 | 0.3064 | 0.8889 |
| 0.0021 | 50.0 | 400 | 0.2989 | 0.8981 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0