---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_mind_model
  results: []
---

<!-- 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6668
- 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: Use adamw_torch_fused 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        | 1.0   | 4    | 2.6480          | 0.0354   |
| No log        | 2.0   | 8    | 2.6528          | 0.0354   |
| 2.6393        | 3.0   | 12   | 2.6578          | 0.0442   |
| 2.6393        | 4.0   | 16   | 2.6518          | 0.0531   |
| 2.6261        | 5.0   | 20   | 2.6490          | 0.0708   |
| 2.6261        | 6.0   | 24   | 2.6534          | 0.0354   |
| 2.6261        | 7.0   | 28   | 2.6562          | 0.0708   |
| 2.6252        | 8.0   | 32   | 2.6635          | 0.0796   |
| 2.6252        | 9.0   | 36   | 2.6670          | 0.0708   |
| 2.6144        | 10.0  | 40   | 2.6668          | 0.0708   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1