---
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_da0.4
  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_da0.4

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: 2.0085
- Wer: 0.1892

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 17.5459       | 13.16  | 250  | 3.5740          | 1.0    |
| 3.1637        | 26.32  | 500  | 3.2268          | 1.0    |
| 2.4912        | 39.47  | 750  | 1.4668          | 0.8590 |
| 0.2685        | 52.63  | 1000 | 1.2848          | 0.2469 |
| 0.0883        | 65.79  | 1250 | 1.4088          | 0.2302 |
| 0.0559        | 78.95  | 1500 | 1.5663          | 0.2196 |
| 0.0386        | 92.11  | 1750 | 1.7690          | 0.2063 |
| 0.0289        | 105.26 | 2000 | 1.7150          | 0.2114 |
| 0.0244        | 118.42 | 2250 | 1.8159          | 0.2106 |
| 0.018         | 131.58 | 2500 | 1.8855          | 0.2038 |
| 0.0147        | 144.74 | 2750 | 1.8758          | 0.2042 |
| 0.0121        | 157.89 | 3000 | 2.1326          | 0.2012 |
| 0.0105        | 171.05 | 3250 | 1.9975          | 0.1897 |
| 0.0093        | 184.21 | 3500 | 1.9094          | 0.1905 |
| 0.0079        | 197.37 | 3750 | 2.0668          | 0.1909 |
| 0.0082        | 210.53 | 4000 | 2.0085          | 0.1892 |


### Framework versions

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