---
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_da1
  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_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: 2.3273
- Wer: 0.1747

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.3928       | 5.43  | 250  | 4.5566          | 1.0    |
| 3.4003        | 10.87 | 500  | 3.2320          | 1.0    |
| 2.9641        | 16.3  | 750  | 2.5134          | 1.0    |
| 0.9965        | 21.74 | 1000 | 1.2335          | 0.4165 |
| 0.2103        | 27.17 | 1250 | 1.5883          | 0.2012 |
| 0.1252        | 32.61 | 1500 | 1.5291          | 0.1837 |
| 0.0911        | 38.04 | 1750 | 1.8433          | 0.1901 |
| 0.0717        | 43.48 | 2000 | 1.9624          | 0.1858 |
| 0.0609        | 48.91 | 2250 | 1.9417          | 0.1781 |
| 0.0488        | 54.35 | 2500 | 2.0794          | 0.1751 |
| 0.041         | 59.78 | 2750 | 2.2785          | 0.1837 |
| 0.0357        | 65.22 | 3000 | 2.1884          | 0.1709 |
| 0.0325        | 70.65 | 3250 | 2.2440          | 0.1764 |
| 0.0286        | 76.09 | 3500 | 2.2743          | 0.1764 |
| 0.0263        | 81.52 | 3750 | 2.2614          | 0.1730 |
| 0.0256        | 86.96 | 4000 | 2.3273          | 0.1747 |


### Framework versions

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