---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Audio_CREMA
  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. -->

# Audio_CREMA

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: 0.8274
- Accuracy: 0.7909
- Weighted f1: 0.7913
- Micro f1: 0.7909
- Macro f1: 0.7909
- Weighted recall: 0.7909
- Micro recall: 0.7909
- Macro recall: 0.7945
- Weighted precision: 0.8014
- Micro precision: 0.7909
- Macro precision: 0.7976

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 1.0002        | 1.0   | 55   | 1.0265          | 0.5477   | 0.5159      | 0.5477   | 0.5169   | 0.5477          | 0.5477       | 0.5486       | 0.5338             | 0.5477          | 0.5341          |
| 0.8613        | 2.0   | 110  | 0.9630          | 0.5795   | 0.5540      | 0.5795   | 0.5558   | 0.5795          | 0.5795       | 0.5825       | 0.5737             | 0.5795          | 0.5718          |
| 0.7676        | 3.0   | 165  | 0.8474          | 0.6659   | 0.6655      | 0.6659   | 0.6624   | 0.6659          | 0.6659       | 0.6629       | 0.6746             | 0.6659          | 0.6713          |
| 0.6886        | 4.0   | 220  | 0.9269          | 0.6318   | 0.6203      | 0.6318   | 0.6198   | 0.6318          | 0.6318       | 0.6351       | 0.6581             | 0.6318          | 0.6506          |
| 0.6536        | 5.0   | 275  | 0.7114          | 0.7341   | 0.7364      | 0.7341   | 0.7350   | 0.7341          | 0.7341       | 0.7360       | 0.7472             | 0.7341          | 0.7424          |
| 0.4429        | 6.0   | 330  | 0.7026          | 0.7432   | 0.7419      | 0.7432   | 0.7406   | 0.7432          | 0.7432       | 0.7425       | 0.7417             | 0.7432          | 0.7399          |
| 0.3755        | 7.0   | 385  | 0.6925          | 0.7682   | 0.7679      | 0.7682   | 0.7680   | 0.7682          | 0.7682       | 0.7717       | 0.7743             | 0.7682          | 0.7712          |
| 0.3603        | 8.0   | 440  | 0.7445          | 0.7591   | 0.7608      | 0.7591   | 0.7604   | 0.7591          | 0.7591       | 0.7610       | 0.7740             | 0.7591          | 0.7716          |
| 0.296         | 9.0   | 495  | 0.7235          | 0.7614   | 0.7577      | 0.7614   | 0.7590   | 0.7614          | 0.7614       | 0.7669       | 0.7718             | 0.7614          | 0.7685          |
| 0.2854        | 10.0  | 550  | 0.6988          | 0.7818   | 0.7832      | 0.7818   | 0.7824   | 0.7818          | 0.7818       | 0.7840       | 0.7923             | 0.7818          | 0.7891          |
| 0.2655        | 11.0  | 605  | 0.7530          | 0.7568   | 0.7526      | 0.7568   | 0.7539   | 0.7568          | 0.7568       | 0.7618       | 0.7632             | 0.7568          | 0.7605          |
| 0.1359        | 12.0  | 660  | 0.7503          | 0.7955   | 0.7974      | 0.7955   | 0.7972   | 0.7955          | 0.7955       | 0.7997       | 0.8110             | 0.7955          | 0.8069          |
| 0.1258        | 13.0  | 715  | 0.8318          | 0.7659   | 0.7634      | 0.7659   | 0.7638   | 0.7659          | 0.7659       | 0.7710       | 0.7808             | 0.7659          | 0.7767          |
| 0.0731        | 14.0  | 770  | 0.8758          | 0.7727   | 0.7718      | 0.7727   | 0.7715   | 0.7727          | 0.7727       | 0.7766       | 0.7883             | 0.7727          | 0.7846          |
| 0.0676        | 15.0  | 825  | 0.8274          | 0.7909   | 0.7913      | 0.7909   | 0.7909   | 0.7909          | 0.7909       | 0.7945       | 0.8014             | 0.7909          | 0.7976          |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1