---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: my_awesome_lang_class_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: 0.21236230110159118
---

<!-- 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_lang_class_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: 2.3072
- Accuracy: 0.2124

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.597         | 1.0   | 51   | 2.5777          | 0.1481   |
| 2.4608        | 1.99  | 102  | 2.4484          | 0.1567   |
| 2.4352        | 2.99  | 153  | 2.4153          | 0.1548   |
| 2.3965        | 4.0   | 205  | 2.3796          | 0.1897   |
| 2.363         | 5.0   | 256  | 2.3622          | 0.1922   |
| 2.3369        | 5.99  | 307  | 2.3496          | 0.1854   |
| 2.292         | 6.99  | 358  | 2.3286          | 0.2038   |
| 2.2788        | 8.0   | 410  | 2.3170          | 0.2075   |
| 2.2537        | 9.0   | 461  | 2.3090          | 0.2044   |
| 2.241         | 9.95  | 510  | 2.3072          | 0.2124   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0