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---
base_model: microsoft/wavlm-base
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavlm-base_3
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-base_3
This model is a fine-tuned version of [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6534
- Accuracy: 0.8974
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 2
- seed: 0
- 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: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2236 | 1.24 | 100 | 12.8495 | 0.4467 |
| 0.0514 | 2.48 | 200 | 16.3078 | 0.2677 |
| 0.0 | 3.72 | 300 | 17.5651 | 0.2597 |
| 0.3252 | 4.95 | 400 | 15.0382 | 0.1912 |
| 1.0577 | 6.19 | 500 | 0.6534 | 0.8974 |
| 0.6973 | 7.43 | 600 | 0.7352 | 0.1026 |
| 0.6939 | 8.67 | 700 | 0.6210 | 0.8974 |
| 0.6944 | 9.91 | 800 | 0.7129 | 0.1026 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0.post302
- Datasets 2.14.5
- Tokenizers 0.13.3
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