---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-NST2-unfreeze-constanti-low-lr
  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-unfreeze-constanti-low-lr

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3562
- Wer: 8.5519

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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1901        | 0.05  | 1000  | 0.3069          | 14.8233 |
| 0.1323        | 0.1   | 2000  | 0.2687          | 11.2885 |
| 0.1137        | 0.15  | 3000  | 0.2620          | 10.8324 |
| 0.1022        | 0.2   | 4000  | 0.2976          | 9.0080  |
| 0.0937        | 0.25  | 5000  | 0.2584          | 9.5781  |
| 0.0875        | 0.3   | 6000  | 0.2704          | 20.2965 |
| 0.0592        | 1.05  | 7000  | 0.2751          | 9.0080  |
| 0.0488        | 1.1   | 8000  | 0.2778          | 8.6659  |
| 0.0475        | 1.15  | 9000  | 0.2792          | 9.4641  |
| 0.0439        | 1.2   | 10000 | 0.2880          | 8.3238  |
| 0.0425        | 1.25  | 11000 | 0.2954          | 8.5519  |
| 0.0416        | 1.3   | 12000 | 0.2896          | 20.2965 |
| 0.0289        | 2.05  | 13000 | 0.2990          | 7.9818  |
| 0.0229        | 2.1   | 14000 | 0.3027          | 7.4116  |
| 0.0248        | 2.15  | 15000 | 0.2968          | 8.6659  |
| 0.0225        | 2.2   | 16000 | 0.3100          | 8.5519  |
| 0.0222        | 2.25  | 17000 | 0.3132          | 9.3501  |
| 0.0219        | 2.3   | 18000 | 0.3230          | 7.6397  |
| 0.0162        | 3.04  | 19000 | 0.3380          | 9.8062  |
| 0.0132        | 3.09  | 20000 | 0.3562          | 8.5519  |


### Framework versions

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