---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-minds-1
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: minds14
      type: minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7610619469026548
---

<!-- 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-finetuned-minds-1

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4208
- Accuracy: 0.7611

## 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: 5e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6059        | 1.0   | 57   | 2.5954          | 0.0973   |
| 2.5183        | 2.0   | 114  | 2.5787          | 0.0973   |
| 2.5497        | 3.0   | 171  | 2.5629          | 0.1416   |
| 2.3827        | 4.0   | 228  | 2.5407          | 0.1858   |
| 2.309         | 5.0   | 285  | 2.3023          | 0.2301   |
| 2.0098        | 6.0   | 342  | 2.0528          | 0.3540   |
| 1.797         | 7.0   | 399  | 1.8558          | 0.4602   |
| 1.4416        | 8.0   | 456  | 1.6847          | 0.5841   |
| 1.3491        | 9.0   | 513  | 1.4911          | 0.6991   |
| 1.3468        | 10.0  | 570  | 1.4208          | 0.7611   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2