---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- dataset_whisper
metrics:
- wer
model-index:
- name: Transcriber-small
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: dataset_whisper
      type: dataset_whisper
      config: default
      split: test
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 97.23577235772358
---

<!-- 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. -->

# Transcriber-small

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the dataset_whisper dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0153
- Wer: 97.2358

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.6006        | 4.02   | 100  | 2.6681          | 99.9350  |
| 1.6004        | 8.04   | 200  | 2.1138          | 107.2846 |
| 1.0072        | 12.06  | 300  | 1.9609          | 129.9187 |
| 0.5229        | 16.08  | 400  | 2.0901          | 119.0894 |
| 0.2155        | 20.1   | 500  | 2.2948          | 105.9187 |
| 0.0743        | 24.12  | 600  | 2.3731          | 100.6829 |
| 0.0292        | 28.14  | 700  | 2.5375          | 118.0813 |
| 0.0169        | 32.16  | 800  | 2.5601          | 108.0650 |
| 0.0121        | 36.18  | 900  | 2.6491          | 102.7642 |
| 0.008         | 40.2   | 1000 | 2.6436          | 94.3415  |
| 0.0046        | 44.22  | 1100 | 2.7131          | 89.8211  |
| 0.0021        | 48.24  | 1200 | 2.7516          | 96.9106  |
| 0.0012        | 52.26  | 1300 | 2.7878          | 95.3496  |
| 0.0009        | 56.28  | 1400 | 2.8137          | 97.6260  |
| 0.0008        | 60.3   | 1500 | 2.8333          | 94.2439  |
| 0.0007        | 64.32  | 1600 | 2.8514          | 90.1463  |
| 0.0006        | 68.34  | 1700 | 2.8667          | 95.3821  |
| 0.0006        | 72.36  | 1800 | 2.8813          | 98.0488  |
| 0.0005        | 76.38  | 1900 | 2.8932          | 98.8618  |
| 0.0005        | 80.4   | 2000 | 2.9056          | 98.9268  |
| 0.0004        | 84.42  | 2100 | 2.9156          | 96.7805  |
| 0.0004        | 88.44  | 2200 | 2.9251          | 96.7805  |
| 0.0004        | 92.46  | 2300 | 2.9343          | 97.8211  |
| 0.0003        | 96.48  | 2400 | 2.9439          | 97.8537  |
| 0.0003        | 100.5  | 2500 | 2.9516          | 97.1057  |
| 0.0003        | 104.52 | 2600 | 2.9597          | 98.1138  |
| 0.0003        | 108.54 | 2700 | 2.9671          | 96.4228  |
| 0.0003        | 112.56 | 2800 | 2.9733          | 99.1870  |
| 0.0003        | 116.58 | 2900 | 2.9791          | 102.2764 |
| 0.0003        | 120.6  | 3000 | 2.9860          | 101.2033 |
| 0.0002        | 124.62 | 3100 | 2.9903          | 98.9919  |
| 0.0002        | 128.64 | 3200 | 2.9953          | 98.3415  |
| 0.0002        | 132.66 | 3300 | 2.9996          | 99.8699  |
| 0.0002        | 136.68 | 3400 | 3.0034          | 100.1301 |
| 0.0002        | 140.7  | 3500 | 3.0070          | 98.7317  |
| 0.0002        | 144.72 | 3600 | 3.0093          | 97.1382  |
| 0.0002        | 148.74 | 3700 | 3.0118          | 98.3740  |
| 0.0002        | 152.76 | 3800 | 3.0136          | 96.8130  |
| 0.0002        | 156.78 | 3900 | 3.0153          | 96.8780  |
| 0.0002        | 160.8  | 4000 | 3.0153          | 97.2358  |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.14.1
- Tokenizers 0.13.3