---
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_da0.05
  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_da0.05

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: 4.9499
- Wer: 1.1098

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 32.094        | 83.33   | 250  | 3.6861          | 1.0    |
| 3.223         | 166.67  | 500  | 3.1064          | 1.0    |
| 3.0141        | 250.0   | 750  | 3.0722          | 1.0    |
| 2.6901        | 333.33  | 1000 | 2.8675          | 1.0    |
| 1.7283        | 416.67  | 1250 | 3.2044          | 1.0436 |
| 0.9791        | 500.0   | 1500 | 3.4905          | 1.0666 |
| 0.6506        | 583.33  | 1750 | 3.7132          | 1.0560 |
| 0.3895        | 666.67  | 2000 | 4.1587          | 1.0824 |
| 0.2399        | 750.0   | 2250 | 4.4319          | 1.1012 |
| 0.1794        | 833.33  | 2500 | 4.4773          | 1.0995 |
| 0.139         | 916.67  | 2750 | 4.6309          | 1.0871 |
| 0.1026        | 1000.0  | 3000 | 4.6925          | 1.0628 |
| 0.0807        | 1083.33 | 3250 | 4.8052          | 1.0824 |
| 0.0611        | 1166.67 | 3500 | 4.8086          | 1.0953 |
| 0.0539        | 1250.0  | 3750 | 4.8570          | 1.0995 |
| 0.0524        | 1333.33 | 4000 | 4.9499          | 1.1098 |


### Framework versions

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