---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- coscan-speech2
metrics:
- accuracy
base_model: facebook/wav2vec2-base
model-index:
- name: wav2vec2-base-coscan-no-area
  results:
  - task:
      type: audio-classification
      name: Audio Classification
    dataset:
      name: Coscan Speech
      type: NbAiLab/coscan-speech
    metrics:
    - type: accuracy
      value: 0.8360824410790649
      name: Test Accuracy
    - type: accuracy
      value: 0.9485961489524133
      name: Validation Accuracy
---

<!-- 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. -->

# wav2vec2-base-coscan-no-area

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the coscan-speech2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3398
- Accuracy: 0.9486

## 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: 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0015        | 1.0   | 6468 | 0.3398          | 0.9486   |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 2.4.1.dev0
- Tokenizers 0.12.1