transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer dataset:common_voice_13_0 base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper-small-model-FullFinetuning-train-test
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: fa
      split: test
      args: fa
    metrics:
    - name: Wer
      type: wer
      value: 96.96969696969697
---

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# Whisper-small-model-FullFinetuning-train-test

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6703
- Wer: 96.9697

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.131         | 0.05  | 100  | 2.2796          | 100.0    |
| 0.6661        | 0.1   | 200  | 2.1839          | 96.9697  |
| 0.5889        | 0.15  | 300  | 2.1523          | 107.5758 |
| 0.5005        | 0.2   | 400  | 1.9232          | 107.5758 |
| 0.421         | 0.25  | 500  | 1.9957          | 101.5152 |
| 0.4363        | 0.3   | 600  | 1.9424          | 96.9697  |
| 0.3583        | 0.35  | 700  | 1.9280          | 95.4545  |
| 0.2703        | 0.4   | 800  | 2.0008          | 93.9394  |
| 0.2836        | 0.45  | 900  | 1.9656          | 90.9091  |
| 0.2948        | 0.5   | 1000 | 1.7947          | 100.0    |
| 0.2236        | 0.55  | 1100 | 1.5250          | 100.0    |
| 0.2029        | 0.6   | 1200 | 1.8172          | 95.4545  |
| 0.1811        | 0.65  | 1300 | 1.8721          | 90.9091  |
| 0.1186        | 0.7   | 1400 | 1.7841          | 96.9697  |
| 0.1765        | 0.75  | 1500 | 1.7462          | 95.4545  |
| 0.1328        | 0.8   | 1600 | 1.7392          | 100.0    |
| 0.1428        | 0.85  | 1700 | 1.7447          | 100.0    |
| 0.1634        | 1.02  | 1800 | 1.6684          | 90.9091  |
| 0.1678        | 1.07  | 1900 | 1.6602          | 101.5152 |
| 0.1826        | 1.12  | 2000 | 1.6703          | 96.9697  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
