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---
library_name: transformers
language:
- vi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small vn - pbl4
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: vi
split: None
args: 'config: vi, split: test'
metrics:
- name: Wer
type: wer
value: 27.821033008005262
---
<!-- 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 vn - pbl4
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7314
- Wer: 27.8210
## 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: 8
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0252 | 5.7471 | 1000 | 0.6066 | 28.1171 |
| 0.0006 | 11.4943 | 2000 | 0.6882 | 27.6017 |
| 0.0003 | 17.2414 | 3000 | 0.7211 | 27.9088 |
| 0.0002 | 22.9885 | 4000 | 0.7314 | 27.8210 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.4.0
- Datasets 3.2.0
- Tokenizers 0.21.0
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