---
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_da0.9
  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_lr1e-4_at0.8_da0.9

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: 2.2030
- Wer: 0.1756

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 15.3627       | 6.1   | 250  | 3.8053          | 1.0    |
| 3.1688        | 12.2  | 500  | 3.1948          | 1.0    |
| 2.7881        | 18.29 | 750  | 1.6319          | 1.0047 |
| 0.3364        | 24.39 | 1000 | 0.9451          | 0.2704 |
| 0.1193        | 30.49 | 1250 | 1.3362          | 0.2089 |
| 0.0741        | 36.59 | 1500 | 1.8263          | 0.1914 |
| 0.0511        | 42.68 | 1750 | 1.8832          | 0.1747 |
| 0.0369        | 48.78 | 2000 | 1.9675          | 0.1794 |
| 0.0256        | 54.88 | 2250 | 2.2933          | 0.1820 |
| 0.0194        | 60.98 | 2500 | 2.3546          | 0.1875 |
| 0.0151        | 67.07 | 2750 | 2.3144          | 0.1773 |
| 0.0126        | 73.17 | 3000 | 2.1852          | 0.1713 |
| 0.0104        | 79.27 | 3250 | 2.2503          | 0.1756 |
| 0.0095        | 85.37 | 3500 | 2.2030          | 0.1756 |


### Framework versions

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