---
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_da0.025
  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_da0.025

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: 3.9947
- Wer: 1.0205

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 36.9594       | 125.0  | 250  | 12.4193         | 1.0    |
| 5.8739        | 250.0  | 500  | 3.2963          | 1.0    |
| 3.1532        | 375.0  | 750  | 3.1231          | 1.0    |
| 3.0639        | 500.0  | 1000 | 3.1060          | 1.0    |
| 3.013         | 625.0  | 1250 | 3.1074          | 1.0    |
| 2.9755        | 750.0  | 1500 | 3.1334          | 1.0    |
| 2.94          | 875.0  | 1750 | 3.1535          | 1.0    |
| 2.8802        | 1000.0 | 2000 | 3.0883          | 1.0    |
| 2.474         | 1125.0 | 2250 | 2.8111          | 1.0009 |
| 1.3378        | 1250.0 | 2500 | 3.0612          | 1.0038 |
| 0.7759        | 1375.0 | 2750 | 3.4681          | 1.0068 |
| 0.594         | 1500.0 | 3000 | 3.6791          | 1.0337 |
| 0.5034        | 1625.0 | 3250 | 3.8161          | 1.0226 |
| 0.4518        | 1750.0 | 3500 | 3.8285          | 1.0081 |
| 0.4139        | 1875.0 | 3750 | 3.9486          | 1.0201 |
| 0.3953        | 2000.0 | 4000 | 3.9947          | 1.0205 |


### Framework versions

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