peft tensorboard safetensors generated_from_trainer automatic-speech-recognition ja dataset:common_voice_16_1 base_model:openai/whisper-small license:mit region:us
---
library_name: peft
tags:
- generated_from_trainer
datasets:
- common_voice_16_1
base_model: openai/whisper-small
model-index:
- name: whisper-small-lora-CV16-JP
  results: []
license: mit
language:
- ja
pipeline_tag: automatic-speech-recognition
metrics:
- wer
---

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

This model was trained from on the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8686
## Model description

Whisper small common voice 16.1 japanese - (Work in progress- this is a test run)

## Intended uses & limitations

test - windows 8-bit/lora
## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.621         | 0.42  | 500  | 0.8686          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu118
- Datasets 2.16.2.dev0
- Tokenizers 0.15.1