---
license: apache-2.0
base_model: facebook/data2vec-audio-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: Testing_for_EEG
  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: 0.07964601769911504
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Testing_for_EEG

This model is a fine-tuned version of [facebook/data2vec-audio-base](https://huggingface.co/facebook/data2vec-audio-base) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6516
- Accuracy: 0.0796

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.8    | 3    | 2.6381          | 0.0796   |
| No log        | 1.8667 | 7    | 2.6388          | 0.0796   |
| 2.6382        | 2.9333 | 11   | 2.6407          | 0.0796   |
| 2.6382        | 4.0    | 15   | 2.6433          | 0.0973   |
| 2.6382        | 4.8    | 18   | 2.6489          | 0.0796   |
| 2.6336        | 5.8667 | 22   | 2.6496          | 0.0796   |
| 2.6336        | 6.9333 | 26   | 2.6501          | 0.0796   |
| 2.6384        | 8.0    | 30   | 2.6516          | 0.0796   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1