transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer yue base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us
---
language:
- yue
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base Bisyllabic Jyutping
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Bisyllabic Jyutping

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the AlienKevin/cantone dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3613
- Wer: 41.25

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- training_steps: 2400

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1093        | 0.08  | 400  | 0.3231          | 51.0417 |
| 0.0389        | 0.15  | 800  | 0.2922          | 40.4861 |
| 0.0237        | 0.23  | 1200 | 0.3020          | 37.7778 |
| 0.0131        | 0.3   | 1600 | 0.3561          | 42.7083 |
| 0.01          | 0.38  | 2000 | 0.3817          | 44.6528 |
| 0.0095        | 0.46  | 2400 | 0.3613          | 41.25   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0
- Datasets 2.14.5
- Tokenizers 0.15.1
