<!-- 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. -->
hubert-large-ll60k-finetuned-ravdess-v4
This model is a fine-tuned version of facebook/hubert-large-ll60k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0831
- Accuracy: 0.625
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0806 | 1.0 | 18 | 2.0768 | 0.1493 |
| 2.0707 | 2.0 | 36 | 2.0653 | 0.1771 |
| 2.0551 | 3.0 | 54 | 2.0475 | 0.1771 |
| 2.0223 | 4.0 | 72 | 2.0066 | 0.2153 |
| 1.8973 | 5.0 | 90 | 1.8130 | 0.2882 |
| 1.8547 | 6.0 | 108 | 1.8352 | 0.2847 |
| 1.7718 | 7.0 | 126 | 1.8253 | 0.2847 |
| 1.722 | 8.0 | 144 | 1.7302 | 0.2986 |
| 1.7004 | 9.0 | 162 | 1.7978 | 0.3160 |
| 1.6574 | 10.0 | 180 | 1.6873 | 0.3507 |
| 1.6387 | 11.0 | 198 | 1.7008 | 0.3576 |
| 1.5605 | 12.0 | 216 | 1.5569 | 0.4340 |
| 1.488 | 13.0 | 234 | 1.4882 | 0.4444 |
| 1.4243 | 14.0 | 252 | 1.4232 | 0.4653 |
| 1.3775 | 15.0 | 270 | 1.4478 | 0.4410 |
| 1.3716 | 16.0 | 288 | 1.3412 | 0.5035 |
| 1.2768 | 17.0 | 306 | 1.3833 | 0.4688 |
| 1.2841 | 18.0 | 324 | 1.3048 | 0.5069 |
| 1.2193 | 19.0 | 342 | 1.2395 | 0.5521 |
| 1.202 | 20.0 | 360 | 1.2025 | 0.5660 |
| 1.169 | 21.0 | 378 | 1.2574 | 0.5312 |
| 1.164 | 22.0 | 396 | 1.1877 | 0.5521 |
| 1.0749 | 23.0 | 414 | 1.1508 | 0.5764 |
| 1.0779 | 24.0 | 432 | 1.1783 | 0.5556 |
| 1.0732 | 25.0 | 450 | 1.1438 | 0.5625 |
| 1.016 | 26.0 | 468 | 1.1971 | 0.5590 |
| 1.022 | 27.0 | 486 | 1.1014 | 0.6042 |
| 1.0345 | 28.0 | 504 | 1.0626 | 0.6215 |
| 1.0081 | 29.0 | 522 | 1.0928 | 0.6181 |
| 1.0036 | 30.0 | 540 | 1.0831 | 0.625 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
