---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- St4n/new-2
metrics:
- wer
model-index:
- name: Whisper Small En - Stan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: new-2
      type: St4n/new-2
      config: default
      split: None
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 8.513708513708513
---

<!-- 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 En - Stan

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the new-2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1269
- Wer: 8.5137

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 200
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0026        | 30.77  | 200  | 0.0885          | 3.0303 |
| 0.0001        | 61.54  | 400  | 0.1035          | 8.8023 |
| 0.0           | 92.31  | 600  | 0.1082          | 8.8023 |
| 0.0           | 123.08 | 800  | 0.1111          | 8.5137 |
| 0.0           | 153.85 | 1000 | 0.1128          | 8.5137 |
| 0.0           | 184.62 | 1200 | 0.1143          | 8.5137 |
| 0.0           | 215.38 | 1400 | 0.1153          | 8.5137 |
| 0.0           | 246.15 | 1600 | 0.1162          | 8.5137 |
| 0.0           | 276.92 | 1800 | 0.1169          | 8.5137 |
| 0.0           | 307.69 | 2000 | 0.1176          | 8.5137 |
| 0.0           | 338.46 | 2200 | 0.1196          | 8.5137 |
| 0.0           | 369.23 | 2400 | 0.1211          | 8.5137 |
| 0.0           | 400.0  | 2600 | 0.1217          | 8.5137 |
| 0.0           | 430.77 | 2800 | 0.1221          | 8.5137 |
| 0.0           | 461.54 | 3000 | 0.1224          | 8.5137 |
| 0.0           | 492.31 | 3200 | 0.1225          | 8.5137 |
| 0.0           | 523.08 | 3400 | 0.1227          | 8.5137 |
| 0.0           | 553.85 | 3600 | 0.1228          | 8.5137 |
| 0.0           | 584.62 | 3800 | 0.1229          | 8.5137 |
| 0.0           | 615.38 | 4000 | 0.1230          | 8.5137 |
| 0.0           | 646.15 | 4200 | 0.1253          | 8.5137 |
| 0.0           | 676.92 | 4400 | 0.1263          | 8.5137 |
| 0.0           | 707.69 | 4600 | 0.1265          | 8.5137 |
| 0.0           | 738.46 | 4800 | 0.1267          | 8.5137 |
| 0.0           | 769.23 | 5000 | 0.1266          | 8.5137 |
| 0.0           | 800.0  | 5200 | 0.1267          | 8.5137 |
| 0.0           | 830.77 | 5400 | 0.1267          | 8.5137 |
| 0.0           | 861.54 | 5600 | 0.1269          | 8.5137 |
| 0.0           | 892.31 | 5800 | 0.1269          | 8.5137 |
| 0.0           | 923.08 | 6000 | 0.1269          | 8.5137 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2