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---
base_model: microsoft/unispeech-sat-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: unispeech-sat-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. -->
# unispeech-sat-base-finetuned-common_voice
This model is a fine-tuned version of [microsoft/unispeech-sat-base](https://huggingface.co./microsoft/unispeech-sat-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0013
- Accuracy: 1.0
- F1: 1.0
- Recall: 1.0
- Precision: 1.0
- Mcc: 1.0
- Auc: 1.0
## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:|
| 0.1326 | 1.0 | 50 | 0.0283 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 |
| 0.1323 | 2.0 | 100 | 0.0450 | 0.9925 | 0.9925 | 0.9925 | 0.9928 | 0.9907 | 0.9994 |
| 0.0499 | 3.0 | 150 | 0.0081 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 |
| 0.0183 | 4.0 | 200 | 0.0037 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.024 | 5.0 | 250 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0326 | 6.0 | 300 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0172 | 7.0 | 350 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0053 | 8.0 | 400 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0034 | 9.0 | 450 | 0.0050 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 |
| 0.014 | 10.0 | 500 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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