---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.6_da1
  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_at0.6_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: 1.4542
- Wer: 0.1867

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 14.9488       | 4.24  | 250  | 3.6144          | 1.0    |
| 3.1468        | 8.47  | 500  | 3.2251          | 1.0    |
| 2.5166        | 12.71 | 750  | 1.3839          | 0.9603 |
| 0.4698        | 16.95 | 1000 | 0.6829          | 0.2909 |
| 0.2122        | 21.19 | 1250 | 0.9930          | 0.2217 |
| 0.1236        | 25.42 | 1500 | 1.1644          | 0.2140 |
| 0.0898        | 29.66 | 1750 | 1.0494          | 0.2076 |
| 0.0664        | 33.9  | 2000 | 1.1845          | 0.2093 |
| 0.0521        | 38.14 | 2250 | 1.2057          | 0.2089 |
| 0.0417        | 42.37 | 2500 | 1.3375          | 0.1914 |
| 0.0359        | 46.61 | 2750 | 1.5455          | 0.1880 |
| 0.0315        | 50.85 | 3000 | 1.3454          | 0.1884 |
| 0.0267        | 55.08 | 3250 | 1.2789          | 0.1944 |
| 0.0239        | 59.32 | 3500 | 1.3917          | 0.1909 |
| 0.0223        | 63.56 | 3750 | 1.4291          | 0.1897 |
| 0.0202        | 67.8  | 4000 | 1.4542          | 0.1867 |


### Framework versions

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