---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.2_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_at0.2_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: 1.0942
- Wer: 0.1674

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 17.4656       | 3.91  | 250  | 3.8210          | 1.0    |
| 3.2203        | 7.81  | 500  | 3.1655          | 1.0    |
| 2.5403        | 11.72 | 750  | 1.2547          | 0.9979 |
| 0.5746        | 15.62 | 1000 | 0.5996          | 0.5088 |
| 0.2573        | 19.53 | 1250 | 0.7483          | 0.2046 |
| 0.152         | 23.44 | 1500 | 0.9229          | 0.1862 |
| 0.1082        | 27.34 | 1750 | 0.9192          | 0.1833 |
| 0.0748        | 31.25 | 2000 | 1.0565          | 0.1747 |
| 0.0603        | 35.16 | 2250 | 0.9710          | 0.1815 |
| 0.0485        | 39.06 | 2500 | 1.0599          | 0.1704 |
| 0.0399        | 42.97 | 2750 | 1.0942          | 0.1730 |
| 0.034         | 46.88 | 3000 | 1.0842          | 0.1670 |
| 0.0309        | 50.78 | 3250 | 1.0670          | 0.1632 |
| 0.0269        | 54.69 | 3500 | 1.1369          | 0.1649 |
| 0.0244        | 58.59 | 3750 | 1.0229          | 0.1666 |
| 0.0228        | 62.5  | 4000 | 1.0942          | 0.1674 |


### Framework versions

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