---
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_da0.5
  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_da0.5

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: 2.3736
- Wer: 0.1858

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 20.81         | 10.87  | 250  | 3.8675          | 1.0    |
| 3.2992        | 21.74  | 500  | 3.1858          | 1.0    |
| 3.0813        | 32.61  | 750  | 3.0758          | 1.0    |
| 2.3718        | 43.48  | 1000 | 1.3480          | 0.8266 |
| 0.3075        | 54.35  | 1250 | 1.6498          | 0.2290 |
| 0.1081        | 65.22  | 1500 | 1.8213          | 0.2012 |
| 0.0732        | 76.09  | 1750 | 1.8933          | 0.1952 |
| 0.0517        | 86.96  | 2000 | 2.0154          | 0.2059 |
| 0.0386        | 97.83  | 2250 | 2.0444          | 0.1948 |
| 0.0323        | 108.7  | 2500 | 2.2603          | 0.2003 |
| 0.0272        | 119.57 | 2750 | 2.2578          | 0.1952 |
| 0.0234        | 130.43 | 3000 | 2.2854          | 0.1880 |
| 0.0203        | 141.3  | 3250 | 2.3553          | 0.1867 |
| 0.0181        | 152.17 | 3500 | 2.3723          | 0.1905 |
| 0.0165        | 163.04 | 3750 | 2.3793          | 0.1854 |
| 0.016         | 173.91 | 4000 | 2.3736          | 0.1858 |


### Framework versions

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