---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.1_da1
  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_at0.1_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: 1.1584
- Wer: 0.1683

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 19.3795       | 3.91  | 250  | 4.4039          | 1.0    |
| 3.4426        | 7.81  | 500  | 3.2239          | 1.0    |
| 3.1246        | 11.72 | 750  | 3.1005          | 1.0    |
| 2.3409        | 15.62 | 1000 | 1.0214          | 0.8765 |
| 0.6128        | 19.53 | 1250 | 0.6213          | 0.4643 |
| 0.3506        | 23.44 | 1500 | 0.6847          | 0.2409 |
| 0.2498        | 27.34 | 1750 | 0.7219          | 0.2055 |
| 0.1928        | 31.25 | 2000 | 0.9377          | 0.1730 |
| 0.1689        | 35.16 | 2250 | 1.0552          | 0.1794 |
| 0.1437        | 39.06 | 2500 | 0.9440          | 0.1756 |
| 0.1256        | 42.97 | 2750 | 1.1132          | 0.1721 |
| 0.1199        | 46.88 | 3000 | 1.1349          | 0.1777 |
| 0.1087        | 50.78 | 3250 | 1.0542          | 0.1781 |
| 0.1056        | 54.69 | 3500 | 1.1394          | 0.1696 |
| 0.1006        | 58.59 | 3750 | 1.1261          | 0.1696 |
| 0.0933        | 62.5  | 4000 | 1.1584          | 0.1683 |


### Framework versions

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