---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at1_da1-p4
  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_at1_da1-p4

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: 0.6341
- Wer: 0.1039

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.6256       | 5.21  | 250  | 4.2622          | 1.0    |
| 3.3901        | 10.42 | 500  | 3.2209          | 1.0    |
| 3.0963        | 15.62 | 750  | 3.1175          | 1.0    |
| 2.0992        | 20.83 | 1000 | 0.5962          | 0.4402 |
| 0.2069        | 26.04 | 1250 | 0.4456          | 0.1310 |
| 0.0849        | 31.25 | 1500 | 0.4902          | 0.1200 |
| 0.0596        | 36.46 | 1750 | 0.5079          | 0.1176 |
| 0.0437        | 41.67 | 2000 | 0.5362          | 0.1136 |
| 0.0355        | 46.88 | 2250 | 0.5433          | 0.1156 |
| 0.0281        | 52.08 | 2500 | 0.5994          | 0.1136 |
| 0.0238        | 57.29 | 2750 | 0.6018          | 0.1112 |
| 0.02          | 62.5  | 3000 | 0.5970          | 0.1120 |
| 0.0181        | 67.71 | 3250 | 0.6282          | 0.1083 |
| 0.0167        | 72.92 | 3500 | 0.6120          | 0.1075 |
| 0.0145        | 78.12 | 3750 | 0.6404          | 0.1047 |
| 0.014         | 83.33 | 4000 | 0.6341          | 0.1039 |


### Framework versions

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