---
license: apache-2.0
tags:
- hf-asr-leaderboard
- automatic-speech-recognition
- NbAiLab/NST
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-NST2
  results: []
---

<!-- 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-NST2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NBAILAB/NST - NO-CLOSE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2990
- Wer: 7.7537

## 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: 4e-05
- train_batch_size: 96
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1846        | 0.1   | 1000  | 0.3460          | 14.9373 |
| 0.1325        | 0.2   | 2000  | 0.3413          | 11.4025 |
| 0.1135        | 0.3   | 3000  | 0.3428          | 12.6568 |
| 0.0955        | 0.4   | 4000  | 0.3140          | 10.7184 |
| 0.0871        | 0.5   | 5000  | 0.2907          | 9.4641  |
| 0.0774        | 0.6   | 6000  | 0.3019          | 11.4025 |
| 0.041         | 1.1   | 7000  | 0.2897          | 9.0080  |
| 0.0306        | 1.2   | 8000  | 0.3013          | 7.6397  |
| 0.0279        | 1.3   | 9000  | 0.2958          | 9.1220  |
| 0.0239        | 1.4   | 10000 | 0.2990          | 7.7537  |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1