transformers tensorboard safetensors wav2vec2 audio-classification generated_from_trainer base_model:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: laryngitis
  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. -->

# laryngitis

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: 0.7828
- Accuracy: 0.5455

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4888        | 1.0   | 6    | 0.7395          | 0.4091   |
| 0.4714        | 2.0   | 12   | 0.7492          | 0.4545   |
| 0.4298        | 3.0   | 18   | 0.7774          | 0.5      |
| 0.3732        | 4.0   | 24   | 0.7864          | 0.5      |
| 0.352         | 5.0   | 30   | 0.7903          | 0.5      |
| 0.3147        | 6.0   | 36   | 0.8435          | 0.5      |
| 0.2969        | 7.0   | 42   | 0.7719          | 0.5      |
| 0.2902        | 8.0   | 48   | 0.7035          | 0.5909   |
| 0.238         | 9.0   | 54   | 0.7546          | 0.5909   |
| 0.2654        | 10.0  | 60   | 0.7828          | 0.5455   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
