---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.8_da1
  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. -->

# w2v2-base-pretrained_lr5e-5_at0.8_da1

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.2151
- Wer: 0.9633

## 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: 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.3205       | 5.43  | 250  | 8.3965          | 1.0    |
| 4.5608        | 10.87 | 500  | 5.8173          | 1.0    |
| 3.4435        | 16.3  | 750  | 6.0815          | 1.0    |
| 3.2716        | 21.74 | 1000 | 5.0685          | 1.0    |
| 3.1606        | 27.17 | 1250 | 4.2348          | 1.0009 |
| 2.9691        | 32.61 | 1500 | 5.6780          | 1.0009 |
| 2.7899        | 38.04 | 1750 | 5.5722          | 1.0017 |
| 2.6205        | 43.48 | 2000 | 6.3790          | 1.0026 |
| 2.444         | 48.91 | 2250 | 5.4383          | 0.9919 |
| 2.3126        | 54.35 | 2500 | 5.0747          | 0.9940 |
| 2.0991        | 59.78 | 2750 | 5.3164          | 0.9855 |
| 1.8757        | 65.22 | 3000 | 5.7173          | 0.9833 |
| 1.7387        | 70.65 | 3250 | 5.4941          | 0.9940 |
| 1.6081        | 76.09 | 3500 | 5.3666          | 0.9675 |
| 1.53          | 81.52 | 3750 | 5.4622          | 0.9731 |
| 1.4346        | 86.96 | 4000 | 5.2151          | 0.9633 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1