---
base_model: mohammadsp99/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper-small-FullFinetuning-CV-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: 93.93939393939394
language:
- fa
library_name: adapter-transformers
---

<!-- 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. -->

# Whisper-small-FullFinetuning-CV-train-test

This model is a fine-tuned version of [mohammadsp99/whisper-small](https://huggingface.co/mohammadsp99/whisper-small) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4865
- Wer: 37.3
The evaluation was done after training
## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.886         | 0.05  | 100  | 2.1958          | 101.5152 |
| 0.6142        | 0.1   | 200  | 2.2113          | 110.6061 |
| 0.5544        | 0.15  | 300  | 2.2247          | 215.1515 |
| 0.4809        | 0.2   | 400  | 1.8149          | 104.5455 |
| 0.393         | 0.25  | 500  | 1.8802          | 96.9697  |
| 0.4191        | 0.3   | 600  | 1.9056          | 107.5758 |
| 0.3515        | 0.35  | 700  | 1.9166          | 89.3939  |
| 0.2671        | 0.4   | 800  | 1.9010          | 86.3636  |
| 0.2763        | 0.45  | 900  | 1.8574          | 96.9697  |
| 0.2896        | 0.5   | 1000 | 1.8940          | 95.4545  |
| 0.2201        | 0.55  | 1100 | 1.6264          | 96.9697  |
| 0.1937        | 0.6   | 1200 | 1.8990          | 98.4848  |
| 0.1787        | 0.65  | 1300 | 1.7999          | 100.0    |
| 0.1138        | 0.7   | 1400 | 1.8118          | 96.9697  |
| 0.1759        | 0.75  | 1500 | 1.9026          | 93.9394  |
| 0.1276        | 0.8   | 1600 | 1.8715          | 195.4545 |
| 0.1437        | 0.85  | 1700 | 1.7353          | 92.4242  |
| 0.1593        | 1.02  | 1800 | 1.7307          | 95.4545  |
| 0.1617        | 1.07  | 1900 | 1.7732          | 96.9697  |
| 0.1737        | 1.12  | 2000 | 1.7646          | 93.9394  |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3