whisper-small-ja / README.md
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---
language:
- ja
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- Specific-Person-Voice
metrics:
- wer
model-index:
- name: Whisper Small ja - Tohio Uchiyama
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Special
type: Specific-Person-Voice
config: null
split: None
args: 'config: ja, split: train'
metrics:
- name: Wer
type: wer
value: 984.4311377245509
---
<!-- 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 ja - Tohio Uchiyama
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Special dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9332
- Wer: 984.4311
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 2.0 | 10 | 1.1812 | 31.1377 |
| No log | 4.0 | 20 | 0.9332 | 984.4311 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2