---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-speech_commands-v0.02
  results: []
---

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# wav2vec2-base-finetuned-speech_commands-v0.02

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1170
- Accuracy: 0.9759

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9963        | 1.0   | 663  | 0.7316          | 0.9612   |
| 0.4965        | 2.0   | 1326 | 0.2656          | 0.9672   |
| 0.4306        | 3.0   | 1989 | 0.1630          | 0.9720   |
| 0.2901        | 4.0   | 2652 | 0.1283          | 0.9753   |
| 0.2963        | 5.0   | 3315 | 0.1170          | 0.9759   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3