---
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: fineturning-without-pretraining-2
  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: 0.9999353420406052
---

<!-- 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-2

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: 779.5451
- Wer: 0.9999

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 35
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1829.2385     | 4.29  | 500  | 781.0485        | 0.9999 |
| 1459.4001     | 8.58  | 1000 | 777.1782        | 0.9999 |
| 1454.826      | 12.88 | 1500 | 777.3484        | 0.9999 |
| 1448.8867     | 17.17 | 2000 | 788.0052        | 0.9999 |
| 1445.467      | 21.46 | 2500 | 779.9430        | 0.9999 |
| 1438.5691     | 25.75 | 3000 | 786.7927        | 0.9999 |
| 1445.318      | 30.04 | 3500 | 789.1374        | 0.9999 |
| 1442.6181     | 34.33 | 4000 | 779.5451        | 0.9999 |


### Framework versions

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