---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr1e-4_at0.8_da0.3
  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_lr1e-4_at0.8_da0.3

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: 2.2956
- Wer: 0.1811

## 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: 0.0001
- 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: 3500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 21.7228       | 17.86  | 250  | 3.7139          | 1.0    |
| 3.1757        | 35.71  | 500  | 3.1149          | 1.0    |
| 2.8079        | 53.57  | 750  | 1.7093          | 1.0038 |
| 0.301         | 71.43  | 1000 | 1.4764          | 0.2443 |
| 0.0637        | 89.29  | 1250 | 1.7091          | 0.2200 |
| 0.0311        | 107.14 | 1500 | 1.7022          | 0.2055 |
| 0.021         | 125.0  | 1750 | 2.0876          | 0.2016 |
| 0.0154        | 142.86 | 2000 | 2.2718          | 0.1974 |
| 0.0114        | 160.71 | 2250 | 2.1541          | 0.1845 |
| 0.0089        | 178.57 | 2500 | 2.2868          | 0.1854 |
| 0.0074        | 196.43 | 2750 | 2.3831          | 0.1914 |
| 0.0062        | 214.29 | 3000 | 2.2381          | 0.1841 |
| 0.0054        | 232.14 | 3250 | 2.4147          | 0.1824 |
| 0.0056        | 250.0  | 3500 | 2.2956          | 0.1811 |


### Framework versions

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