---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.9_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_at0.9_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: 2.5021
- Wer: 0.1820

## 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: 1000
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.4753       | 6.1   | 250  | 4.2333          | 1.0    |
| 3.358         | 12.2  | 500  | 3.2161          | 1.0    |
| 3.108         | 18.29 | 750  | 3.1259          | 1.0    |
| 2.2419        | 24.39 | 1000 | 1.1771          | 0.7117 |
| 0.2791        | 30.49 | 1250 | 1.5708          | 0.2328 |
| 0.137         | 36.59 | 1500 | 1.7979          | 0.1961 |
| 0.0936        | 42.68 | 1750 | 2.0223          | 0.1948 |
| 0.0723        | 48.78 | 2000 | 2.2080          | 0.1892 |
| 0.0584        | 54.88 | 2250 | 2.1748          | 0.1854 |
| 0.0472        | 60.98 | 2500 | 2.2649          | 0.1828 |
| 0.042         | 67.07 | 2750 | 2.3289          | 0.1880 |
| 0.0349        | 73.17 | 3000 | 2.3042          | 0.1854 |
| 0.032         | 79.27 | 3250 | 2.2214          | 0.1841 |
| 0.0284        | 85.37 | 3500 | 2.3253          | 0.1807 |
| 0.0258        | 91.46 | 3750 | 2.4980          | 0.1815 |
| 0.0238        | 97.56 | 4000 | 2.5021          | 0.1820 |


### Framework versions

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