---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr1e-4_at0.8_da0.6
  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_lr1e-4_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: 2.5777
- Wer: 0.1820

## 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: 0.0001
- 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: 3500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 15.4716       | 8.93   | 250  | 3.5805          | 1.0    |
| 3.156         | 17.86  | 500  | 3.1574          | 1.0    |
| 2.6095        | 26.79  | 750  | 1.2490          | 1.0    |
| 0.2716        | 35.71  | 1000 | 1.6097          | 0.2422 |
| 0.0901        | 44.64  | 1250 | 1.8537          | 0.2085 |
| 0.0526        | 53.57  | 1500 | 1.7249          | 0.2080 |
| 0.0328        | 62.5   | 1750 | 2.2934          | 0.1922 |
| 0.0237        | 71.43  | 2000 | 2.1689          | 0.1948 |
| 0.018         | 80.36  | 2250 | 2.4606          | 0.1918 |
| 0.0144        | 89.29  | 2500 | 2.6943          | 0.1837 |
| 0.0108        | 98.21  | 2750 | 2.5514          | 0.1807 |
| 0.0078        | 107.14 | 3000 | 2.5035          | 0.1858 |
| 0.0064        | 116.07 | 3250 | 2.6022          | 0.1845 |
| 0.0069        | 125.0  | 3500 | 2.5777          | 0.1820 |


### Framework versions

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