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---
base_model: microsoft/wavlm-base-plus
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavelm-study
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. -->
# wavelm-study
This model is a fine-tuned version of [microsoft/wavlm-base-plus](https://huggingface.co/microsoft/wavlm-base-plus) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6466
- Accuracy: 0.8783
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9941 | 1.0 | 30 | 0.9388 | 0.6528 |
| 0.7785 | 2.0 | 60 | 0.7010 | 0.8655 |
| 0.7143 | 3.0 | 90 | 0.6466 | 0.8783 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.16.1
- Tokenizers 0.15.0
|