---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: asr_model
  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. -->

# asr_model

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: 0.2363
- Wer: 0.5153

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.4621        | 2.0   | 1000  | 0.4702          | 0.9741 |
| 0.4612        | 4.0   | 2000  | 0.4621          | 0.9741 |
| 0.4458        | 6.0   | 3000  | 0.4464          | 0.9714 |
| 0.384         | 8.0   | 4000  | 0.3853          | 0.8235 |
| 0.3065        | 10.0  | 5000  | 0.3166          | 0.7829 |
| 0.2861        | 12.0  | 6000  | 0.2809          | 0.6802 |
| 0.248         | 14.0  | 7000  | 0.2677          | 0.6051 |
| 0.2449        | 16.0  | 8000  | 0.2541          | 0.5778 |
| 0.2298        | 18.0  | 9000  | 0.2480          | 0.5710 |
| 0.2281        | 20.0  | 10000 | 0.2418          | 0.5505 |
| 0.216         | 22.0  | 11000 | 0.2420          | 0.5340 |
| 0.2083        | 24.0  | 12000 | 0.2380          | 0.5253 |
| 0.1957        | 26.0  | 13000 | 0.2380          | 0.5209 |
| 0.1985        | 28.0  | 14000 | 0.2360          | 0.5181 |
| 0.2078        | 30.0  | 15000 | 0.2363          | 0.5153 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0