---
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: 2.3043
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5917        | 1.0   | 51   | 2.5829          | 0.1212   |
| 2.446         | 1.99  | 102  | 2.4314          | 0.1548   |
| 2.3832        | 2.99  | 153  | 2.4035          | 0.1499   |
| 2.3799        | 4.0   | 205  | 2.3959          | 0.1585   |
| 2.3082        | 5.0   | 256  | 2.4232          | 0.1646   |
| 2.3123        | 5.99  | 307  | 2.3424          | 0.1720   |
| 2.2871        | 6.99  | 358  | 2.3240          | 0.1769   |
| 2.28          | 8.0   | 410  | 2.3176          | 0.1873   |
| 2.2306        | 9.0   | 461  | 2.3139          | 0.1940   |
| 2.2277        | 9.95  | 510  | 2.3043          | 0.1946   |


### Framework versions

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