---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.3_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_at0.3_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: 1.2363
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 15.0228       | 3.97  | 250  | 4.0018          | 1.0    |
| 3.1757        | 7.94  | 500  | 3.2733          | 1.0    |
| 3.0888        | 11.9  | 750  | 3.0842          | 1.0    |
| 1.8583        | 15.87 | 1000 | 0.8173          | 0.6087 |
| 0.3832        | 19.84 | 1250 | 0.6533          | 0.3520 |
| 0.2105        | 23.81 | 1500 | 0.7165          | 0.2448 |
| 0.1301        | 27.78 | 1750 | 0.9040          | 0.2016 |
| 0.0917        | 31.75 | 2000 | 1.0631          | 0.1961 |
| 0.0674        | 35.71 | 2250 | 1.0216          | 0.1905 |
| 0.0571        | 39.68 | 2500 | 1.1088          | 0.1854 |
| 0.0456        | 43.65 | 2750 | 1.2525          | 0.1747 |
| 0.0387        | 47.62 | 3000 | 1.1236          | 0.1845 |
| 0.034         | 51.59 | 3250 | 1.1696          | 0.1730 |
| 0.0291        | 55.56 | 3500 | 1.2542          | 0.1756 |
| 0.0284        | 59.52 | 3750 | 1.2190          | 0.1760 |
| 0.026         | 63.49 | 4000 | 1.2363          | 0.1773 |


### Framework versions

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