---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- lalipa/jv_id_asr_split
metrics:
- wer
model-index:
- name: hyperparameter
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: lalipa/jv_id_asr_split jv_id_asr_source
      type: lalipa/jv_id_asr_split
      config: jv_id_asr_source
      split: validation
      args: jv_id_asr_source
    metrics:
    - name: Wer
      type: wer
      value: 0.6883827458964245
---

<!-- 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. -->

# hyperparameter

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the lalipa/jv_id_asr_split jv_id_asr_source dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4506
- Wer: 0.6884
- Cer: 0.2050

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
- training_steps: 300

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 3.9694        | 0.1020 | 30   | 3.7782          | 1.8748 | 1.0887 |
| 3.3735        | 0.2041 | 60   | 2.9598          | 1.0019 | 0.4254 |
| 2.5449        | 0.3061 | 90   | 2.1989          | 0.8820 | 0.3221 |
| 1.9987        | 0.4082 | 120  | 1.8648          | 0.8004 | 0.2606 |
| 1.7671        | 0.5102 | 150  | 1.6909          | 0.7619 | 0.2312 |
| 1.6285        | 0.6122 | 180  | 1.5863          | 0.7336 | 0.2245 |
| 1.5475        | 0.7143 | 210  | 1.5251          | 0.7216 | 0.2213 |
| 1.4793        | 0.8163 | 240  | 1.4807          | 0.6942 | 0.2035 |
| 1.5013        | 0.9184 | 270  | 1.4582          | 0.6904 | 0.2057 |
| 1.4438        | 1.0204 | 300  | 1.4506          | 0.6884 | 0.2050 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1
- Datasets 3.0.1
- Tokenizers 0.20.0