---
license: apache-2.0
tags:
- hf-asr-leaderboard
- automatic-speech-recognition
- NbAiLab/NST
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-NST-uf-linlr
  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-medium-NST-uf-linlr

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the NBAILAB/NST - NO-CLOSE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3007
- Wer: 9.1220

## 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: 72
- 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: 1000
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2046        | 0.05  | 1000  | 0.3426          | 15.2794 |
| 0.148         | 0.1   | 2000  | 0.3284          | 10.8324 |
| 0.121         | 0.15  | 3000  | 0.3092          | 12.8848 |
| 0.1089        | 0.2   | 4000  | 0.2808          | 10.4903 |
| 0.0976        | 0.25  | 5000  | 0.2617          | 9.9202  |
| 0.0901        | 0.3   | 6000  | 0.2604          | 21.8928 |
| 0.0834        | 0.35  | 7000  | 0.2877          | 9.3501  |
| 0.0825        | 0.4   | 8000  | 0.2794          | 9.3501  |
| 0.0553        | 1.05  | 9000  | 0.2845          | 9.5781  |
| 0.0472        | 1.1   | 10000 | 0.2814          | 24.1733 |
| 0.0409        | 1.15  | 11000 | 0.3084          | 8.0958  |
| 0.041         | 1.2   | 12000 | 0.2865          | 9.2360  |
| 0.0353        | 1.25  | 13000 | 0.2828          | 6.4994  |
| 0.0348        | 1.3   | 14000 | 0.2708          | 7.5257  |
| 0.0349        | 1.35  | 15000 | 0.2842          | 23.0331 |
| 0.0361        | 1.4   | 16000 | 0.2769          | 10.1482 |
| 0.0249        | 2.04  | 17000 | 0.2935          | 8.8940  |
| 0.0204        | 2.09  | 18000 | 0.2874          | 12.4287 |
| 0.0175        | 2.14  | 19000 | 0.2882          | 12.9989 |
| 0.0197        | 2.19  | 20000 | 0.3007          | 9.1220  |


### Framework versions

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