---
library_name: transformers
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: en-US
      split: train
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.04424778761061947
---

<!-- 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: 2.6519
- Accuracy: 0.0442

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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    | 2.6387          | 0.0708   |
| No log        | 1.9333 | 7    | 2.6374          | 0.0796   |
| 2.6385        | 2.8    | 10   | 2.6409          | 0.0442   |
| 2.6385        | 3.9333 | 14   | 2.6468          | 0.0354   |
| 2.6385        | 4.8    | 17   | 2.6513          | 0.0531   |
| 2.6341        | 5.9333 | 21   | 2.6533          | 0.0265   |
| 2.6341        | 6.8    | 24   | 2.6520          | 0.0531   |
| 2.6341        | 7.9333 | 28   | 2.6515          | 0.0442   |
| 2.6266        | 8.5333 | 30   | 2.6519          | 0.0442   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3