---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.5_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_at0.5_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: 1.6472
- Wer: 0.1786

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.9615       | 4.17  | 250  | 4.3427          | 1.0    |
| 3.3745        | 8.33  | 500  | 3.2218          | 1.0    |
| 3.1073        | 12.5  | 750  | 3.1350          | 1.0    |
| 2.1233        | 16.67 | 1000 | 0.8774          | 0.7915 |
| 0.4649        | 20.83 | 1250 | 0.8879          | 0.3691 |
| 0.2435        | 25.0  | 1500 | 0.8832          | 0.2119 |
| 0.1677        | 29.17 | 1750 | 1.2547          | 0.1871 |
| 0.1148        | 33.33 | 2000 | 1.3004          | 0.1786 |
| 0.0904        | 37.5  | 2250 | 1.2741          | 0.1995 |
| 0.0732        | 41.67 | 2500 | 1.4082          | 0.1747 |
| 0.0613        | 45.83 | 2750 | 1.5234          | 0.1824 |
| 0.0536        | 50.0  | 3000 | 1.4060          | 0.1798 |
| 0.046         | 54.17 | 3250 | 1.5669          | 0.1833 |
| 0.0441        | 58.33 | 3500 | 1.5661          | 0.1807 |
| 0.0392        | 62.5  | 3750 | 1.6374          | 0.1790 |
| 0.0384        | 66.67 | 4000 | 1.6472          | 0.1786 |


### Framework versions

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