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my_awesome_mind_model

Audio Classification
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wav2vec2
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my_awesome_mind_model
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---
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: 0.07079646017699115
---

<!-- 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: 2.6482
- Accuracy: 0.0708

## 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    | 2.6349          | 0.0796   |
| No log        | 1.87  | 7    | 2.6392          | 0.0531   |
| 2.6367        | 2.93  | 11   | 2.6412          | 0.0619   |
| 2.6367        | 4.0   | 15   | 2.6439          | 0.0619   |
| 2.6367        | 4.8   | 18   | 2.6458          | 0.0619   |
| 2.6202        | 5.87  | 22   | 2.6476          | 0.0619   |
| 2.6202        | 6.93  | 26   | 2.6480          | 0.0619   |
| 2.613         | 8.0   | 30   | 2.6482          | 0.0708   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2