---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-nm-nor
  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-nm-nor

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0663
- Wer: 2.7237

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| No log        | 5.5714  | 100  | 0.7192          | 5.0584 |
| 1.5787        | 11.1143 | 200  | 0.0608          | 2.7237 |
| 1.5787        | 16.6857 | 300  | 0.0601          | 2.7237 |
| 0.002         | 22.2286 | 400  | 0.0627          | 2.7237 |
| 0.002         | 27.8    | 500  | 0.0642          | 2.7237 |
| 0.0           | 33.3429 | 600  | 0.0653          | 2.7237 |
| 0.0           | 38.9143 | 700  | 0.0659          | 2.7237 |
| 0.0           | 44.4571 | 800  | 0.0663          | 2.7237 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0