---
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_da0.1
  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_da0.1

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: 4.7430
- Wer: 0.8847

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 32.6282       | 50.0  | 250  | 4.0044          | 1.0    |
| 3.5474        | 100.0 | 500  | 3.1597          | 1.0    |
| 3.0565        | 150.0 | 750  | 3.0680          | 1.0    |
| 2.8909        | 200.0 | 1000 | 3.0005          | 1.0    |
| 2.292         | 250.0 | 1250 | 2.6442          | 0.9991 |
| 1.2329        | 300.0 | 1500 | 2.9696          | 0.9577 |
| 0.6684        | 350.0 | 1750 | 3.4034          | 0.9453 |
| 0.4377        | 400.0 | 2000 | 3.7834          | 0.9389 |
| 0.3292        | 450.0 | 2250 | 3.9480          | 0.9000 |
| 0.2554        | 500.0 | 2500 | 4.3241          | 0.8906 |
| 0.2073        | 550.0 | 2750 | 4.4139          | 0.9047 |
| 0.1762        | 600.0 | 3000 | 4.5423          | 0.9000 |
| 0.1551        | 650.0 | 3250 | 4.5978          | 0.8817 |
| 0.1403        | 700.0 | 3500 | 4.6304          | 0.8757 |
| 0.1286        | 750.0 | 3750 | 4.6839          | 0.8855 |
| 0.1201        | 800.0 | 4000 | 4.7430          | 0.8847 |


### Framework versions

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