File size: 2,116 Bytes
1284989 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
library_name: transformers
language:
- kh
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- google
metrics:
- wer
model-index:
- name: Whisper-Small-kh
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Fleur
type: google
metrics:
- name: Wer
type: wer
value: 19.510040160642568
---
<!-- 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-kh
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Fleur dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2773
- Wer Ortho: 40.6131
- Wer: 19.5100
- Cer: 10.6710
## 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: 64
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.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: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | Cer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:-------:|
| No log | 1.0 | 19 | 0.2679 | 40.6512 | 19.5904 | 10.7011 |
| 0.0006 | 2.0 | 38 | 0.2717 | 40.4037 | 19.5984 | 10.7388 |
| 0.0005 | 2.8649 | 54 | 0.2773 | 40.6131 | 19.5100 | 10.6710 |
### Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 2.14.7
- Tokenizers 0.22.1
|