---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: my_awesome_mind_model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: minds14
      type: minds14
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.19461444308445533
---

<!-- 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. -->

# my_awesome_mind_model

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: 2.3185
- Accuracy: 0.1946

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5962        | 1.0   | 51   | 2.5963          | 0.1346   |
| 2.4773        | 1.99  | 102  | 2.4556          | 0.1561   |
| 2.4457        | 2.99  | 153  | 2.4258          | 0.1695   |
| 2.3907        | 4.0   | 205  | 2.4256          | 0.1622   |
| 2.3532        | 5.0   | 256  | 2.3852          | 0.1756   |
| 2.3148        | 5.99  | 307  | 2.3579          | 0.1836   |
| 2.3114        | 6.99  | 358  | 2.3570          | 0.1848   |
| 2.2891        | 8.0   | 410  | 2.3377          | 0.1848   |
| 2.2785        | 9.0   | 461  | 2.3202          | 0.1909   |
| 2.269         | 9.95  | 510  | 2.3185          | 0.1946   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0