---
license: apache-2.0
base_model: OthmaneJ/distil-wav2vec2
tags:
- generated_from_trainer
datasets:
- OthmaneJ/distil-wav2vec2
metrics:
- accuracy
model-index:
- name: distil-wav2vec2-finetuned-giga-speech
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Giga Speech
      type: OthmaneJ/distil-wav2vec2
      config: xs
      split: train
      args: xs
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8881789137380192
---

<!-- 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. -->

# distil-wav2vec2-finetuned-giga-speech

This model is a fine-tuned version of [OthmaneJ/distil-wav2vec2](https://huggingface.co/OthmaneJ/distil-wav2vec2) on the Giga Speech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4271
- Accuracy: 0.8882

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4425        | 1.0   | 1057 | 1.3045          | 0.5399   |
| 0.796         | 2.0   | 2114 | 0.8516          | 0.7284   |
| 0.9685        | 3.0   | 3171 | 0.5054          | 0.8626   |
| 0.5623        | 4.0   | 4228 | 0.4271          | 0.8882   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3