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

# wav2vec2-tokenizer

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: 0.0005
- Wer: 0.2412

## 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: 0.0003
- 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: 100
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.8291        | 4.0   | 100  | 1.7138          | 0.9862 |
| 1.2768        | 8.0   | 200  | 0.7349          | 0.7488 |
| 0.53          | 12.0  | 300  | 0.2418          | 0.705  |
| 0.2342        | 16.0  | 400  | 0.1818          | 0.7362 |
| 0.1375        | 20.0  | 500  | 0.1053          | 0.73   |
| 0.1286        | 24.0  | 600  | 0.0886          | 0.7063 |
| 0.0978        | 28.0  | 700  | 0.0634          | 0.74   |
| 0.0952        | 32.0  | 800  | 0.0642          | 0.6963 |
| 0.088         | 36.0  | 900  | 0.0674          | 0.7025 |
| 0.0802        | 40.0  | 1000 | 0.0140          | 0.2587 |
| 0.0624        | 44.0  | 1100 | 0.0185          | 0.1862 |
| 0.029         | 48.0  | 1200 | 0.0234          | 0.2725 |
| 0.0176        | 52.0  | 1300 | 0.0072          | 0.2275 |
| 0.016         | 56.0  | 1400 | 0.0036          | 0.265  |
| 0.0047        | 60.0  | 1500 | 0.0019          | 0.235  |
| 0.0066        | 64.0  | 1600 | 0.0014          | 0.2075 |
| 0.0041        | 68.0  | 1700 | 0.0009          | 0.2712 |
| 0.0019        | 72.0  | 1800 | 0.0008          | 0.2863 |
| 0.002         | 76.0  | 1900 | 0.0007          | 0.2888 |
| 0.0031        | 80.0  | 2000 | 0.0006          | 0.2863 |
| 0.0032        | 84.0  | 2100 | 0.0006          | 0.2762 |
| 0.0026        | 88.0  | 2200 | 0.0005          | 0.2325 |
| 0.0019        | 92.0  | 2300 | 0.0005          | 0.2362 |
| 0.0046        | 96.0  | 2400 | 0.0005          | 0.2412 |
| 0.0018        | 100.0 | 2500 | 0.0005          | 0.2412 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.14.5
- Tokenizers 0.15.2