---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.6_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_at0.6_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: 1.4078
- Wer: 0.1662

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 25.5608       | 4.24  | 250  | 20.1943         | 1.0    |
| 5.6218        | 8.47  | 500  | 3.4933          | 1.0    |
| 3.134         | 12.71 | 750  | 3.1332          | 1.0    |
| 3.0842        | 16.95 | 1000 | 3.1196          | 1.0    |
| 2.6714        | 21.19 | 1250 | 1.4095          | 0.9932 |
| 0.5642        | 25.42 | 1500 | 0.6028          | 0.4327 |
| 0.2724        | 29.66 | 1750 | 0.7355          | 0.2396 |
| 0.1676        | 33.9  | 2000 | 0.9693          | 0.2264 |
| 0.1247        | 38.14 | 2250 | 1.0615          | 0.2008 |
| 0.0945        | 42.37 | 2500 | 1.2612          | 0.1841 |
| 0.0784        | 46.61 | 2750 | 1.1492          | 0.1850 |
| 0.0672        | 50.85 | 3000 | 1.3113          | 0.1751 |
| 0.0567        | 55.08 | 3250 | 1.3594          | 0.1721 |
| 0.0507        | 59.32 | 3500 | 1.4195          | 0.1721 |
| 0.0478        | 63.56 | 3750 | 1.3916          | 0.1670 |
| 0.0445        | 67.8  | 4000 | 1.4078          | 0.1662 |


### Framework versions

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