---
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
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# 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