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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: 0.0560
- Accuracy: 0.99
- F1: 0.9900
- Recall: 0.99
- Precision: 0.9902
- Mcc: 0.9875
- Auc: 0.9983
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.7394 | 1.0 | 200 | 0.2528 | 0.95 | 0.9497 | 0.95 | 0.9554 | 0.9390 | 0.9952 |
| 0.0013 | 2.0 | 400 | 0.0069 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 |
| 0.0435 | 3.0 | 600 | 0.0962 | 0.985 | 0.9850 | 0.9850 | 0.9852 | 0.9813 | 0.9987 |
| 0.1172 | 4.0 | 800 | 0.0434 | 0.995 | 0.9950 | 0.9950 | 0.9950 | 0.9938 | 0.9993 |
| 0.0005 | 5.0 | 1000 | 0.0496 | 0.9925 | 0.9925 | 0.9925 | 0.9926 | 0.9906 | 0.9984 |
| 0.0006 | 6.0 | 1200 | 0.0652 | 0.99 | 0.9900 | 0.99 | 0.9901 | 0.9875 | 0.9991 |
| 0.0004 | 7.0 | 1400 | 0.0267 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 0.9982 |
| 0.0003 | 8.0 | 1600 | 0.0423 | 0.9925 | 0.9925 | 0.9925 | 0.9926 | 0.9906 | 0.9982 |
| 0.0003 | 9.0 | 1800 | 0.0549 | 0.9875 | 0.9875 | 0.9875 | 0.9877 | 0.9844 | 0.9982 |
| 0.0003 | 10.0 | 2000 | 0.0560 | 0.99 | 0.9900 | 0.99 | 0.9902 | 0.9875 | 0.9983 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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