peft safetensors whisper common voice windows fleurs japanese anime automatic-speech-recognition ja dataset:google/fleurs dataset:joujiboi/japanese-anime-speech dataset:mozilla-foundation/common_voice_16_1 base_model:openai/whisper-small license:apache-2.0 region:us
---
license: apache-2.0
library_name: peft
tags:
- whisper
- common voice
- peft
- windows
- fleurs
- japanese
- anime
datasets:
- google/fleurs
- joujiboi/japanese-anime-speech
- mozilla-foundation/common_voice_16_1
base_model: openai/whisper-small
model-index:
- name: whisper-small-CV16-GF-AS-jp
  results: []
language:
- ja
metrics:
- wer
pipeline_tag: automatic-speech-recognition
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-small-CV16-GF-AS-jp

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7695
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the joujiboi/japanese-anime-speech dataset.

## Model description

3 concantenated datasets LoRA peft on a windows 10 no linux.  (Work in progress- this is a test run)

## Intended uses & limitations

Test run for large model.

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3266        | 1.0   | 500  | 0.7695          |


### 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