---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at1_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_at1_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: 2.3753
- Wer: 0.1837

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.9508       | 6.1   | 250  | 4.5541          | 1.0    |
| 3.4223        | 12.2  | 500  | 3.2365          | 1.0    |
| 3.1022        | 18.29 | 750  | 3.1107          | 1.0    |
| 2.0891        | 24.39 | 1000 | 1.2943          | 0.4930 |
| 0.2477        | 30.49 | 1250 | 1.4675          | 0.2208 |
| 0.1323        | 36.59 | 1500 | 1.8152          | 0.2067 |
| 0.0908        | 42.68 | 1750 | 1.8821          | 0.1931 |
| 0.0721        | 48.78 | 2000 | 2.1984          | 0.2008 |
| 0.0584        | 54.88 | 2250 | 2.0544          | 0.1927 |
| 0.0483        | 60.98 | 2500 | 2.0092          | 0.1845 |
| 0.0437        | 67.07 | 2750 | 2.1545          | 0.1837 |
| 0.0347        | 73.17 | 3000 | 2.3775          | 0.1918 |
| 0.0331        | 79.27 | 3250 | 2.4051          | 0.1880 |
| 0.0302        | 85.37 | 3500 | 2.3556          | 0.1790 |
| 0.0279        | 91.46 | 3750 | 2.3822          | 0.1858 |
| 0.026         | 97.56 | 4000 | 2.3753          | 0.1837 |


### Framework versions

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