---
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_da0.7
  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_da0.7

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: 2.2042
- Wer: 0.1884

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 24.3422       | 7.81   | 250  | 5.6070          | 1.0    |
| 3.5981        | 15.62  | 500  | 3.2535          | 1.0    |
| 3.1121        | 23.44  | 750  | 3.1577          | 1.0    |
| 3.0596        | 31.25  | 1000 | 3.1214          | 1.0    |
| 3.0143        | 39.06  | 1250 | 2.9603          | 1.0    |
| 1.4861        | 46.88  | 1500 | 1.2406          | 0.4007 |
| 0.2223        | 54.69  | 1750 | 1.3926          | 0.2324 |
| 0.1147        | 62.5   | 2000 | 1.5275          | 0.2136 |
| 0.0775        | 70.31  | 2250 | 1.8277          | 0.1986 |
| 0.0601        | 78.12  | 2500 | 1.9747          | 0.1944 |
| 0.0479        | 85.94  | 2750 | 2.0632          | 0.1909 |
| 0.042         | 93.75  | 3000 | 2.1333          | 0.1991 |
| 0.0353        | 101.56 | 3250 | 2.1743          | 0.1982 |
| 0.0315        | 109.38 | 3500 | 2.1585          | 0.1939 |
| 0.0274        | 117.19 | 3750 | 2.1521          | 0.1914 |
| 0.0279        | 125.0  | 4000 | 2.2042          | 0.1884 |


### Framework versions

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