---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

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: 1.9132
- Accuracy: 0.6351
- F1: 0.6301
- Precision: 0.6315
- Recall: 0.6351

## 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: 2e-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
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.586         | 1.0   | 855   | 0.6272          | 0.6316   | 0.5289 | 0.5719    | 0.6316 |
| 0.6905        | 2.0   | 1710  | 0.5821          | 0.6520   | 0.5420 | 0.4804    | 0.6520 |
| 0.5642        | 3.0   | 2565  | 0.6012          | 0.6497   | 0.5396 | 0.4769    | 0.6497 |
| 0.6263        | 4.0   | 3420  | 0.6040          | 0.6526   | 0.5903 | 0.6403    | 0.6526 |
| 0.7556        | 5.0   | 4275  | 0.6088          | 0.6485   | 0.5406 | 0.4838    | 0.6485 |
| 0.4614        | 6.0   | 5130  | 0.6061          | 0.6614   | 0.6348 | 0.6523    | 0.6614 |
| 0.4232        | 7.0   | 5985  | 0.6184          | 0.6456   | 0.6401 | 0.6355    | 0.6456 |
| 0.519         | 8.0   | 6840  | 0.6186          | 0.6538   | 0.5449 | 0.4874    | 0.6538 |
| 0.4847        | 9.0   | 7695  | 0.6226          | 0.6421   | 0.5652 | 0.5948    | 0.6421 |
| 0.5505        | 10.0  | 8550  | 0.6857          | 0.6363   | 0.5903 | 0.6241    | 0.6363 |
| 0.5499        | 11.0  | 9405  | 0.6684          | 0.6491   | 0.6462 | 0.6470    | 0.6491 |
| 0.2869        | 12.0  | 10260 | 0.7500          | 0.6468   | 0.6341 | 0.6389    | 0.6468 |
| 0.2607        | 13.0  | 11115 | 0.9291          | 0.6351   | 0.6354 | 0.6357    | 0.6351 |
| 0.3495        | 14.0  | 11970 | 1.1298          | 0.6444   | 0.6415 | 0.6396    | 0.6444 |
| 0.2483        | 15.0  | 12825 | 1.3714          | 0.6246   | 0.6181 | 0.6320    | 0.6246 |
| 0.3764        | 16.0  | 13680 | 1.4325          | 0.6515   | 0.6454 | 0.6475    | 0.6515 |
| 0.373         | 17.0  | 14535 | 1.6233          | 0.6491   | 0.6473 | 0.6457    | 0.6491 |
| 0.0677        | 18.0  | 15390 | 1.7408          | 0.6450   | 0.6434 | 0.6429    | 0.6450 |
| 0.0665        | 19.0  | 16245 | 1.8868          | 0.6351   | 0.6296 | 0.6316    | 0.6351 |
| 0.0044        | 20.0  | 17100 | 1.9132          | 0.6351   | 0.6301 | 0.6315    | 0.6351 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1