transformers pytorch whisper automatic-speech-recognition generated_from_trainer base_model:kosamit/whisper-tiny-ja endpoints_compatible region:us
---
tags:
- generated_from_trainer
base_model: kosamit/whisper-tiny-ja
metrics:
- wer
model-index:
- name: whisper-tiny-ja-alicia
  results: []
---

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「アリシア」という単語を学習させたモデル。

# whisper-tiny-ja-alicia

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5542
- Wer: 85.7143

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0311        | 3.33  | 10   | 0.3741          | 85.7143 |
| 0.0012        | 6.67  | 20   | 0.4759          | 85.7143 |
| 0.0001        | 10.0  | 30   | 0.5351          | 85.7143 |
| 0.0           | 13.33 | 40   | 0.5542          | 85.7143 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.1.1+cu118
- Datasets 2.16.1
- Tokenizers 0.13.3
