---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- razhan/DOLMA-speech
metrics:
- bleu
model-index:
- name: whisper-base-hawrami
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: razhan/DOLMA-speech hawrami
      type: razhan/DOLMA-speech
      args: hawrami
    metrics:
    - name: Bleu
      type: bleu
      value: 0.403603847823992
---

<!-- 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-hawrami

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the razhan/DOLMA-speech hawrami dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0851
- Chrf: 13.3279
- Bleu: 0.4036

## 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: 256
- 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 | Chrf    | Bleu   |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 4.056         | 1.0   | 40   | 3.7037          | 12.1151 | 0.0829 |
| 3.4175        | 2.0   | 80   | 3.2226          | 11.2675 | 0.1153 |
| 3.1704        | 3.0   | 120  | 3.1141          | 12.9709 | 0.2803 |
| 3.0286        | 4.0   | 160  | 3.0851          | 13.3279 | 0.4036 |


### Framework versions

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