---
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_da0.6
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v2-base-pretrained_lr5e-5_at0.8_da0.6

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: 2.3139
- Wer: 0.1773

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 22.3022       | 8.93   | 250  | 14.1336         | 1.0    |
| 7.1613        | 17.86  | 500  | 12.5928         | 1.0    |
| 4.3974        | 26.79  | 750  | 12.3385         | 1.0    |
| 4.139         | 35.71  | 1000 | 9.3127          | 1.0    |
| 3.3971        | 44.64  | 1250 | 3.0328          | 1.0    |
| 1.9421        | 53.57  | 1500 | 1.4361          | 0.7381 |
| 0.2784        | 62.5   | 1750 | 1.4964          | 0.2896 |
| 0.1222        | 71.43  | 2000 | 1.7459          | 0.2559 |
| 0.0769        | 80.36  | 2250 | 2.0649          | 0.2255 |
| 0.0559        | 89.29  | 2500 | 2.2779          | 0.1892 |
| 0.0432        | 98.21  | 2750 | 2.2997          | 0.1901 |
| 0.036         | 107.14 | 3000 | 2.2112          | 0.1871 |
| 0.0309        | 116.07 | 3250 | 2.3675          | 0.1867 |
| 0.028         | 125.0  | 3500 | 2.3204          | 0.1820 |
| 0.0252        | 133.93 | 3750 | 2.3129          | 0.1803 |
| 0.0238        | 142.86 | 4000 | 2.3139          | 0.1773 |


### Framework versions

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