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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xwhisper-kh-base
results: []
---
<!-- 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. -->
# xwhisper-kh-base
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: 0.2711
- Wer: 74.0769
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.8338 | 1.0 | 1087 | 0.4122 | 90.5307 |
| 0.3136 | 2.0 | 2174 | 0.3022 | 80.1699 |
| 0.2199 | 3.0 | 3261 | 0.2599 | 76.6601 |
| 0.1675 | 4.0 | 4348 | 0.2483 | 74.3577 |
| 0.1294 | 5.0 | 5435 | 0.2483 | 72.6309 |
| 0.1001 | 6.0 | 6522 | 0.2555 | 74.8982 |
| 0.0759 | 7.0 | 7609 | 0.2711 | 74.0769 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3
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