---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
datasets:
- PhanithLIM/ams-speech-dataset
- openslr/openslr
- google/fleurs
- PhanithLIM/kh-wmc
- PhanithLIM/wmc-international-news
- PhanithLIM/rfi-news-dataset
- PhanithLIM/aakanee-kh
- rinabuoy/khm-asr-open
- seanghay/khmer_grkpp_speech
- seanghay/khmer_mpwt_speech
- seanghay/km-speech-corpus
model-index:
- name: Khmer Whisper Small PhanithLIM
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Google FLEURS
      type: google/fleurs
      config: km_kh
      split: test
    metrics:
    - name: CER
      type: cer
      value: 14.414
---

<!-- 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-aug-20-april-lightning-v1

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: 0.1044
- Wer: 85.2539

## 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: constant
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.5768        | 1.0    | 1424  | 0.2062          | 98.4412 |
| 0.1775        | 2.0    | 2848  | 0.1505          | 89.7549 |
| 0.1321        | 3.0    | 4272  | 0.1304          | 86.5233 |
| 0.109         | 4.0    | 5696  | 0.1184          | 87.7905 |
| 0.0935        | 5.0    | 7120  | 0.1108          | 83.8661 |
| 0.0815        | 6.0    | 8544  | 0.1072          | 85.3635 |
| 0.0722        | 7.0    | 9968  | 0.1058          | 84.4405 |
| 0.0644        | 8.0    | 11392 | 0.1049          | 82.3862 |
| 0.0575        | 9.0    | 12816 | 0.1049          | 84.2761 |
| 0.0521        | 9.9933 | 14230 | 0.1044          | 85.2539 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.2.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.1