---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: IDAT_aug_red_696_Wav2Vec
  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. -->

# IDAT_aug_red_696_Wav2Vec

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: 0.5564
- Accuracy: 0.7667

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6862        | 0.97  | 17   | 0.6526          | 0.675    |
| 0.609         | 2.0   | 35   | 0.6533          | 0.6917   |
| 0.5659        | 2.97  | 52   | 0.7129          | 0.6583   |
| 0.6223        | 4.0   | 70   | 0.5106          | 0.7833   |
| 0.5163        | 4.97  | 87   | 0.7914          | 0.7      |
| 0.6306        | 6.0   | 105  | 0.5960          | 0.75     |
| 0.5651        | 6.97  | 122  | 0.7364          | 0.5583   |
| 0.7081        | 8.0   | 140  | 0.7070          | 0.5      |
| 0.699         | 8.97  | 157  | 0.6951          | 0.5      |
| 0.6958        | 10.0  | 175  | 0.6934          | 0.5      |
| 0.6978        | 10.97 | 192  | 0.6916          | 0.5      |
| 0.6786        | 12.0  | 210  | 0.6940          | 0.5      |
| 0.6981        | 12.97 | 227  | 0.6932          | 0.5      |
| 0.6931        | 14.0  | 245  | 0.6933          | 0.5      |
| 0.6939        | 14.97 | 262  | 0.6931          | 0.5      |
| 0.6935        | 16.0  | 280  | 0.6931          | 0.5      |
| 0.6972        | 16.97 | 297  | 0.6931          | 0.5      |
| 0.6935        | 18.0  | 315  | 0.6931          | 0.5      |
| 0.6931        | 18.97 | 332  | 0.6951          | 0.5      |
| 0.6955        | 20.0  | 350  | 0.6921          | 0.7      |
| 0.6992        | 20.97 | 367  | 0.6843          | 0.5      |
| 0.6785        | 22.0  | 385  | 0.6919          | 0.5      |
| 0.6661        | 22.97 | 402  | 0.6317          | 0.6417   |
| 0.597         | 24.0  | 420  | 0.5620          | 0.75     |
| 0.5849        | 24.97 | 437  | 0.6103          | 0.75     |
| 0.5955        | 26.0  | 455  | 0.6245          | 0.725    |
| 0.4777        | 26.97 | 472  | 0.5215          | 0.7833   |
| 0.4726        | 28.0  | 490  | 0.5657          | 0.775    |
| 0.4487        | 28.97 | 507  | 0.5306          | 0.7833   |
| 0.4478        | 30.0  | 525  | 0.6591          | 0.7333   |
| 0.5039        | 30.97 | 542  | 0.5304          | 0.7833   |
| 0.5173        | 32.0  | 560  | 0.7111          | 0.7      |
| 0.5266        | 32.97 | 577  | 0.5587          | 0.7667   |
| 0.4677        | 34.0  | 595  | 0.5515          | 0.7667   |
| 0.4775        | 34.97 | 612  | 0.5116          | 0.7917   |
| 0.4651        | 36.0  | 630  | 0.5450          | 0.7667   |
| 0.4738        | 36.97 | 647  | 0.5371          | 0.7833   |
| 0.4862        | 38.0  | 665  | 0.5497          | 0.7667   |
| 0.4695        | 38.86 | 680  | 0.5564          | 0.7667   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3