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

# output_model

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2884
- Wer: 0.4752

## 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: 0.0001
- train_batch_size: 8
- 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
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 2.8783        | 2.4752  | 500  | 2.7618          | 0.9999 |
| 1.4069        | 4.9505  | 1000 | 1.0853          | 0.6936 |
| 0.6264        | 7.4257  | 1500 | 0.9955          | 0.6014 |
| 0.3864        | 9.9010  | 2000 | 1.0460          | 0.5675 |
| 0.2714        | 12.3762 | 2500 | 0.9830          | 0.5422 |
| 0.2099        | 14.8515 | 3000 | 1.0333          | 0.5296 |
| 0.1615        | 17.3267 | 3500 | 1.1575          | 0.5203 |
| 0.1248        | 19.8020 | 4000 | 1.1311          | 0.4956 |
| 0.1032        | 22.2772 | 4500 | 1.3206          | 0.4953 |
| 0.0834        | 24.7525 | 5000 | 1.2094          | 0.4855 |
| 0.0655        | 27.2277 | 5500 | 1.2966          | 0.4763 |
| 0.052         | 29.7030 | 6000 | 1.2884          | 0.4752 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1