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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wavlm-base-plus-ft
results: []
datasets:
- mazkooleg/0-9up_google_speech_commands_augmented_raw
---
<!-- 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-plus-ft
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: 0.0093
- Accuracy: 0.9973
## 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: 1e-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: 5
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.087 | 1.0 | 8558 | 0.9947 | 0.0216 |
| 0.0439 | 2.0 | 17117 | 0.9964 | 0.0117 |
| 0.0626 | 3.0 | 25675 | 0.9973 | 0.0093 |
| 0.0396 | 4.0 | 34232 | 0.9964 | 0.0097 |
| 0.0417 | 5.0 | 42790 | 0.9964 | 0.0123 |
### Framework versions
- Transformers 4.27.3
- Pytorch 1.11.0
- Datasets 2.10.1
- Tokenizers 0.12.1 |