---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
model-index:
- name: whisper-base-me
  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-base-me

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5421
- Mazanderani Wer: 0.6836
- Mazanderani Cer: 0.2510
- Gilaki Wer: 0.9606
- Gilaki Cer: 0.3818
- Zazaki Wer: 0.7623
- Zazaki Cer: 0.3182
- Laki Kurdish Wer: 0.6037
- Laki Kurdish Cer: 0.1653
- Talysh Wer: 0.9167
- Talysh Cer: 0.5
- Hawrami Wer: 0.4145
- Hawrami Cer: 0.0865
- Southern Kurdish Wer: 0.5610
- Southern Kurdish Cer: 0.1721
- Avg Wer: 0.7003
- Avg Cer: 0.2678

## 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: 128
- eval_batch_size: 128
- seed: 42
- 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: 100
- num_epochs: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mazanderani Wer | Mazanderani Cer | Gilaki Wer | Gilaki Cer | Zazaki Wer | Zazaki Cer | Laki Kurdish Wer | Laki Kurdish Cer | Talysh Wer | Talysh Cer | Hawrami Wer | Hawrami Cer | Southern Kurdish Wer | Southern Kurdish Cer | Avg Wer | Avg Cer |
|:-------------:|:-----:|:----:|:---------------:|:---------------:|:---------------:|:----------:|:----------:|:----------:|:----------:|:----------------:|:----------------:|:----------:|:----------:|:-----------:|:-----------:|:--------------------:|:--------------------:|:-------:|:-------:|
| 0.5933        | 1.0   | 164  | 0.7337          | 0.8884          | 0.3139          | 0.9969     | 0.3853     | 0.9485     | 0.7335     | 0.7857           | 0.2461           | 0.9167     | 0.5        | 0.5257      | 0.1162      | 0.6900               | 0.2137               | 0.8217  | 0.3584  |
| 0.4436        | 2.0   | 328  | 0.5930          | 0.7514          | 0.2939          | 0.9723     | 0.3818     | 0.8382     | 0.4153     | 0.6487           | 0.1846           | 0.9167     | 0.5        | 0.4419      | 0.0933      | 0.5951               | 0.1798               | 0.7378  | 0.2927  |
| 0.387         | 3.0   | 492  | 0.5509          | 0.6821          | 0.2436          | 0.9523     | 0.3735     | 0.7892     | 0.3340     | 0.6094           | 0.1678           | 0.9167     | 0.5        | 0.4230      | 0.0891      | 0.5705               | 0.1871               | 0.7062  | 0.2707  |
| 0.3575        | 4.0   | 656  | 0.5421          | 0.6836          | 0.2510          | 0.9606     | 0.3818     | 0.7623     | 0.3182     | 0.6037           | 0.1653           | 0.9167     | 0.5        | 0.4145      | 0.0865      | 0.5610               | 0.1721               | 0.7003  | 0.2678  |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0