---
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: fineturning-without-pretraining-3
  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: 1.231604810552179
---

<!-- 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-3

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: 3.0417
- Wer: 1.2316

## 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: 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.4746        | 4.27  | 500  | 2.6868          | 1.0    |
| 2.5662        | 8.55  | 1000 | 2.4297          | 1.0371 |
| 2.3434        | 12.82 | 1500 | 2.3182          | 1.1941 |
| 2.134         | 17.09 | 2000 | 2.3792          | 1.1749 |
| 1.8502        | 21.37 | 2500 | 2.6371          | 1.1072 |
| 1.5697        | 25.64 | 3000 | 2.9421          | 1.1907 |
| 1.3814        | 29.91 | 3500 | 3.0417          | 1.2316 |


### Framework versions

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