---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: finetuning2
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_1_0
      type: common_voice_1_0
      config: en
      split: validation
      args: en
    metrics:
    - name: Wer
      type: wer
      value: 0.4213759213759214
---

<!-- 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. -->

# finetuning2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_1_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6883
- Wer: 0.4214

## 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: 0.0001
- train_batch_size: 32
- 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_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.5277        | 4.27  | 500  | 2.8353          | 0.9863 |
| 1.2768        | 8.55  | 1000 | 0.7019          | 0.5581 |
| 0.4511        | 12.82 | 1500 | 0.6201          | 0.4726 |
| 0.2591        | 17.09 | 2000 | 0.6428          | 0.4469 |
| 0.1854        | 21.37 | 2500 | 0.6901          | 0.4388 |
| 0.1386        | 25.64 | 3000 | 0.6933          | 0.4259 |
| 0.111         | 29.91 | 3500 | 0.6883          | 0.4214 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2