---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: ft-wav2vec2-with-minds
  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: 0.11504424778761062
---

<!-- 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. -->

# ft-wav2vec2-with-minds

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: 2.6358
- Accuracy: 0.1150

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 2.6358          | 0.1150   |
| No log        | 2.0   | 4    | 2.6403          | 0.1062   |
| No log        | 3.0   | 6    | 2.6474          | 0.0796   |
| No log        | 4.0   | 8    | 2.6491          | 0.0442   |
| 2.6359        | 5.0   | 10   | 2.6499          | 0.0531   |
| 2.6359        | 6.0   | 12   | 2.6521          | 0.0531   |
| 2.6359        | 7.0   | 14   | 2.6526          | 0.0442   |
| 2.6359        | 8.0   | 16   | 2.6522          | 0.0354   |
| 2.6359        | 9.0   | 18   | 2.6520          | 0.0354   |
| 2.625         | 10.0  | 20   | 2.6521          | 0.0442   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0