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---
language:
- km
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- openslr
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Khmer - Seanghay Yath
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Google FLEURS
type: google/fleurs
config: km_kh
split: all
metrics:
- name: Wer
type: wer
value: 1.0704381586245146
---
<!-- 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 Small Khmer - Seanghay Yath
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Google FLEURS & OpenSLR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4484
- Wer: 1.0704
## 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: 6.25e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2052 | 3.33 | 1000 | 0.3582 | 1.0233 |
| 0.0465 | 6.67 | 2000 | 0.3129 | 1.0105 |
| 0.0089 | 10.0 | 3000 | 0.3977 | 1.0214 |
| 0.0016 | 13.33 | 4000 | 0.4484 | 1.0704 |
### Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.12.1
- Datasets 2.11.1.dev0
- Tokenizers 0.13.3
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