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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: wav2vec2-base-finetuned-common_voice
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. -->
# wav2vec2-base-finetuned-common_voice
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0419
- Accuracy: 0.995
- F1: 0.9950
- Recall: 0.9950
- Precision: 0.9951
- Mcc: 0.9938
- Auc: 0.9987
## 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: 8
- eval_batch_size: 8
- seed: 42
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | Mcc | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.8258 | 1.0 | 200 | 0.7423 | 0.76 | 0.6973 | 0.76 | 0.6699 | 0.7402 | 0.9766 |
| 0.1609 | 2.0 | 400 | 0.1559 | 0.96 | 0.9596 | 0.96 | 0.9644 | 0.9513 | 0.9997 |
| 0.219 | 3.0 | 600 | 0.0864 | 0.9825 | 0.9826 | 0.9825 | 0.9828 | 0.9782 | 0.9983 |
| 0.0049 | 4.0 | 800 | 0.0341 | 0.995 | 0.9950 | 0.9950 | 0.9950 | 0.9938 | 0.9999 |
| 0.0031 | 5.0 | 1000 | 0.1241 | 0.98 | 0.9799 | 0.9800 | 0.9808 | 0.9752 | 0.9989 |
| 0.0021 | 6.0 | 1200 | 0.0394 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9988 |
| 0.0017 | 7.0 | 1400 | 0.0410 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9993 |
| 0.0015 | 8.0 | 1600 | 0.0420 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9987 |
| 0.0013 | 9.0 | 1800 | 0.0418 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9987 |
| 0.0013 | 10.0 | 2000 | 0.0419 | 0.995 | 0.9950 | 0.9950 | 0.9951 | 0.9938 | 0.9987 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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