---
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
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# 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: 1.6691
- Wer: 0.1858

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 14.0341       | 5.43  | 250  | 3.5667          | 1.0    |
| 3.138         | 10.87 | 500  | 3.1976          | 1.0    |
| 3.0471        | 16.3  | 750  | 3.0452          | 1.0    |
| 1.3116        | 21.74 | 1000 | 1.0225          | 0.3358 |
| 0.1806        | 27.17 | 1250 | 1.2151          | 0.2533 |
| 0.1065        | 32.61 | 1500 | 1.2673          | 0.2384 |
| 0.0707        | 38.04 | 1750 | 1.4184          | 0.1888 |
| 0.0547        | 43.48 | 2000 | 1.6087          | 0.1901 |
| 0.0471        | 48.91 | 2250 | 1.4537          | 0.1880 |
| 0.0381        | 54.35 | 2500 | 1.6858          | 0.1845 |
| 0.0307        | 59.78 | 2750 | 1.5607          | 0.1961 |
| 0.0269        | 65.22 | 3000 | 1.6716          | 0.1862 |
| 0.024         | 70.65 | 3250 | 1.5554          | 0.1884 |
| 0.0199        | 76.09 | 3500 | 1.7169          | 0.1850 |
| 0.0187        | 81.52 | 3750 | 1.6661          | 0.1858 |
| 0.0176        | 86.96 | 4000 | 1.6691          | 0.1858 |


### Framework versions

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