---
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_da0.7
  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_at0.8_da0.7

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: 1.7538
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 16.4265       | 7.81   | 250  | 3.9246          | 1.0    |
| 3.1637        | 15.62  | 500  | 3.1545          | 1.0    |
| 2.2078        | 23.44  | 750  | 1.2345          | 0.6258 |
| 0.2629        | 31.25  | 1000 | 1.0938          | 0.2862 |
| 0.1013        | 39.06  | 1250 | 1.2497          | 0.2482 |
| 0.061         | 46.88  | 1500 | 1.4009          | 0.1956 |
| 0.0438        | 54.69  | 1750 | 1.4359          | 0.1935 |
| 0.0334        | 62.5   | 2000 | 1.6005          | 0.2003 |
| 0.0256        | 70.31  | 2250 | 1.5475          | 0.1897 |
| 0.0231        | 78.12  | 2500 | 1.6901          | 0.1914 |
| 0.0176        | 85.94  | 2750 | 1.6743          | 0.1961 |
| 0.0164        | 93.75  | 3000 | 1.6498          | 0.1815 |
| 0.0133        | 101.56 | 3250 | 1.7255          | 0.1897 |
| 0.0127        | 109.38 | 3500 | 1.7270          | 0.1875 |
| 0.011         | 117.19 | 3750 | 1.7833          | 0.1918 |
| 0.0111        | 125.0  | 4000 | 1.7538          | 0.1892 |


### Framework versions

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