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---
base_model: microsoft/wavlm-base
tags:
- generated_from_trainer
task: audio-classification
model-index:
- name: wavlm_finetuned_emodb
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. -->
# wavlm_finetuned_emodb
This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9254
- Uar: 0.8148
- Acc: 0.8529
## Model description
This model predict given audio waveform to one of four common emotion categories: anger, happiness, sadness, and neutral
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Uar | Acc |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 1.3857 | 0.1538 | 1 | 1.3786 | 0.25 | 0.1985 |
| 1.3322 | 0.3077 | 2 | 1.3549 | 0.2914 | 0.2426 |
| 1.3112 | 0.4615 | 3 | 1.3165 | 0.5375 | 0.6103 |
| 1.2981 | 0.6154 | 4 | 1.2905 | 0.5 | 0.6029 |
| 1.1317 | 0.7692 | 5 | 1.2923 | 0.4907 | 0.5956 |
| 1.2078 | 0.9231 | 6 | 1.2619 | 0.5556 | 0.6471 |
| 0.9237 | 1.0769 | 7 | 1.2254 | 0.5741 | 0.6618 |
| 0.8396 | 1.2308 | 8 | 1.2247 | 0.5556 | 0.6471 |
| 1.0354 | 1.3846 | 9 | 1.2076 | 0.5556 | 0.6471 |
| 0.9205 | 1.5385 | 10 | 1.1891 | 0.5833 | 0.6691 |
| 0.9071 | 1.6923 | 11 | 1.1704 | 0.6481 | 0.7206 |
| 0.8132 | 1.8462 | 12 | 1.1988 | 0.6939 | 0.5735 |
| 0.8994 | 2.0 | 13 | 1.1960 | 0.6574 | 0.5221 |
| 0.7924 | 2.1538 | 14 | 1.1579 | 0.6658 | 0.5662 |
| 0.7386 | 2.3077 | 15 | 1.1401 | 0.6944 | 0.7574 |
| 0.6324 | 2.4615 | 16 | 1.1202 | 0.6111 | 0.6912 |
| 0.7282 | 2.6154 | 17 | 1.1090 | 0.5833 | 0.6691 |
| 0.673 | 2.7692 | 18 | 1.0907 | 0.6111 | 0.6912 |
| 0.623 | 2.9231 | 19 | 1.0578 | 0.7872 | 0.8235 |
| 0.4954 | 3.0769 | 20 | 1.0357 | 0.8475 | 0.8676 |
| 0.5201 | 3.2308 | 21 | 1.0365 | 0.7778 | 0.8235 |
| 0.5608 | 3.3846 | 22 | 1.0346 | 0.75 | 0.8015 |
| 0.6334 | 3.5385 | 23 | 1.0047 | 0.7685 | 0.8162 |
| 0.3737 | 3.6923 | 24 | 0.9585 | 0.8658 | 0.8897 |
| 0.5369 | 3.8462 | 25 | 0.9527 | 0.9178 | 0.8824 |
| 0.3599 | 4.0 | 26 | 0.9682 | 0.8906 | 0.8382 |
| 0.7642 | 4.1538 | 27 | 0.9418 | 0.8951 | 0.8456 |
| 0.4882 | 4.3077 | 28 | 0.9095 | 0.9310 | 0.9265 |
| 0.5011 | 4.4615 | 29 | 0.9378 | 0.8426 | 0.875 |
| 0.3707 | 4.6154 | 30 | 0.9630 | 0.7963 | 0.8382 |
| 0.381 | 4.7692 | 31 | 0.9721 | 0.7870 | 0.8309 |
| 0.2307 | 4.9231 | 32 | 0.9522 | 0.7963 | 0.8382 |
| 0.2829 | 5.0769 | 33 | 0.9598 | 0.7870 | 0.8309 |
| 0.2581 | 5.2308 | 34 | 0.9458 | 0.8056 | 0.8456 |
| 0.4658 | 5.3846 | 35 | 0.9442 | 0.8148 | 0.8529 |
| 0.2133 | 5.5385 | 36 | 0.9524 | 0.7870 | 0.8309 |
| 0.1107 | 5.6923 | 37 | 0.9601 | 0.7870 | 0.8309 |
| 0.3599 | 5.8462 | 38 | 0.9605 | 0.7778 | 0.8235 |
| 0.3085 | 6.0 | 39 | 0.9522 | 0.7918 | 0.8309 |
| 0.2739 | 6.1538 | 40 | 0.9564 | 0.7870 | 0.8309 |
| 0.3279 | 6.3077 | 41 | 0.9582 | 0.7870 | 0.8309 |
| 0.1346 | 6.4615 | 42 | 0.9646 | 0.7685 | 0.8162 |
| 0.1429 | 6.6154 | 43 | 0.9695 | 0.7685 | 0.8162 |
| 0.1 | 6.7692 | 44 | 0.9692 | 0.7685 | 0.8162 |
| 0.1852 | 6.9231 | 45 | 0.9651 | 0.7685 | 0.8162 |
| 0.1028 | 7.0769 | 46 | 0.9378 | 0.8056 | 0.8456 |
| 0.2071 | 7.2308 | 47 | 0.9154 | 0.8195 | 0.8529 |
| 0.1752 | 7.3846 | 48 | 0.8882 | 0.8566 | 0.8824 |
| 0.0907 | 7.5385 | 49 | 0.8704 | 0.8843 | 0.9044 |
| 0.1263 | 7.6923 | 50 | 0.8719 | 0.8798 | 0.8971 |
| 0.068 | 7.8462 | 51 | 0.8738 | 0.8798 | 0.8971 |
| 0.0589 | 8.0 | 52 | 0.8881 | 0.8566 | 0.8824 |
| 0.1494 | 8.1538 | 53 | 0.9001 | 0.8473 | 0.875 |
| 0.1137 | 8.3077 | 54 | 0.9120 | 0.8288 | 0.8603 |
| 0.0522 | 8.4615 | 55 | 0.9212 | 0.8148 | 0.8529 |
| 0.0666 | 8.6154 | 56 | 0.9251 | 0.8148 | 0.8529 |
| 0.0867 | 8.7692 | 57 | 0.9270 | 0.8148 | 0.8529 |
| 0.0764 | 8.9231 | 58 | 0.9264 | 0.8148 | 0.8529 |
| 0.0526 | 9.0769 | 59 | 0.9259 | 0.8148 | 0.8529 |
| 0.2877 | 9.2308 | 60 | 0.9254 | 0.8148 | 0.8529 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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