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---
language:
- zh
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Medium Zh - Kimas
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. -->
# Whisper Medium Zh - Kimas
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0635
- Wer: 100.0
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1461 | 0.28 | 1000 | 0.1406 | 100.0 |
| 0.0803 | 0.57 | 2000 | 0.1181 | 100.0 |
| 0.0715 | 0.85 | 3000 | 0.1039 | 100.0 |
| 0.0255 | 1.14 | 4000 | 0.0925 | 100.0207 |
| 0.0199 | 1.42 | 5000 | 0.0810 | 100.0 |
| 0.027 | 1.7 | 6000 | 0.0767 | 100.0207 |
| 0.0328 | 1.99 | 7000 | 0.0706 | 100.0 |
| 0.0026 | 2.27 | 8000 | 0.0700 | 100.0 |
| 0.0082 | 2.56 | 9000 | 0.0646 | 100.0 |
| 0.0099 | 2.84 | 10000 | 0.0635 | 100.0 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 1.12.1
- Datasets 2.14.6
- Tokenizers 0.14.1
|