---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Lesson1results
  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. -->

# Lesson1results

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0149
- Accuracy: 0.9962
- F1-score: 0.9962
- Recall-score: 0.9962
- Precision-score: 0.9962

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Recall-score | Precision-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------------:|:---------------:|
| 1.1736        | 1.0   | 278  | 0.9850          | 0.7898   | 0.7552   | 0.7898       | 0.7813          |
| 0.4185        | 2.0   | 556  | 0.4326          | 0.9106   | 0.8991   | 0.9106       | 0.9062          |
| 0.3854        | 3.0   | 834  | 0.2507          | 0.9363   | 0.9335   | 0.9363       | 0.9409          |
| 0.2509        | 4.0   | 1112 | 0.1460          | 0.9666   | 0.9665   | 0.9666       | 0.9673          |
| 0.107         | 5.0   | 1390 | 0.1278          | 0.9641   | 0.9640   | 0.9641       | 0.9689          |
| 0.3585        | 6.0   | 1668 | 0.1188          | 0.9758   | 0.9758   | 0.9758       | 0.9764          |
| 0.2611        | 7.0   | 1946 | 0.1148          | 0.9704   | 0.9702   | 0.9704       | 0.9722          |
| 0.2493        | 8.0   | 2224 | 0.0638          | 0.9824   | 0.9824   | 0.9824       | 0.9828          |
| 0.0351        | 9.0   | 2502 | 0.0492          | 0.9887   | 0.9887   | 0.9887       | 0.9890          |
| 0.4708        | 10.0  | 2780 | 0.0479          | 0.9883   | 0.9883   | 0.9883       | 0.9885          |
| 0.2958        | 11.0  | 3058 | 0.0561          | 0.9865   | 0.9865   | 0.9865       | 0.9870          |
| 0.138         | 12.0  | 3336 | 0.0308          | 0.9916   | 0.9916   | 0.9916       | 0.9918          |
| 0.0525        | 13.0  | 3614 | 0.0226          | 0.9944   | 0.9944   | 0.9944       | 0.9944          |
| 0.0332        | 14.0  | 3892 | 0.0293          | 0.9916   | 0.9916   | 0.9916       | 0.9920          |
| 0.0332        | 15.0  | 4170 | 0.0202          | 0.9953   | 0.9953   | 0.9953       | 0.9953          |
| 0.339         | 16.0  | 4448 | 0.0210          | 0.9955   | 0.9955   | 0.9955       | 0.9955          |
| 0.211         | 17.0  | 4726 | 0.0218          | 0.9959   | 0.9959   | 0.9959       | 0.9960          |
| 0.0017        | 18.0  | 5004 | 0.0181          | 0.9964   | 0.9964   | 0.9964       | 0.9964          |
| 0.1646        | 19.0  | 5282 | 0.0166          | 0.9959   | 0.9959   | 0.9959       | 0.9960          |
| 0.0014        | 20.0  | 5560 | 0.0149          | 0.9962   | 0.9962   | 0.9962       | 0.9962          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1