---
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: fineturning-without-pretraining
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_1_0
      type: common_voice_1_0
      config: en
      split: validation
      args: en
    metrics:
    - name: Wer
      type: wer
      value: 1.1837902495797232
---

<!-- 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. -->

# fineturning-without-pretraining

This model is a fine-tuned version of [](https://huggingface.co/) on the common_voice_1_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 812.3214
- Wer: 1.1838

## 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: 16
- 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
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2141.1597     | 2.15  | 500  | 908.3237        | 1.0    |
| 1549.364      | 4.29  | 1000 | 813.9642        | 1.1682 |
| 1442.1247     | 6.44  | 1500 | 788.9472        | 1.5341 |
| 1395.3347     | 8.58  | 2000 | 757.5609        | 1.2662 |
| 1344.5591     | 10.73 | 2500 | 751.7140        | 1.1790 |
| 1289.6164     | 12.88 | 3000 | 746.7259        | 1.2651 |
| 1248.0024     | 15.02 | 3500 | 761.1828        | 1.2634 |
| 1208.4588     | 17.17 | 4000 | 789.4526        | 1.1426 |
| 1162.758      | 19.31 | 4500 | 794.2302        | 1.1521 |
| 1118.2571     | 21.46 | 5000 | 803.2517        | 1.2117 |
| 1097.6801     | 23.61 | 5500 | 812.3214        | 1.1838 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2