---
license: apache-2.0
base_model: rinna/japanese-wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-kanji-base-char-0916
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/tokudai-nishimura-lab/Emoto-ASR-training-log/runs/nc3r560f)
# wav2vec2-kanji-base-char-0916

This model is a fine-tuned version of [rinna/japanese-wav2vec2-base](https://huggingface.co/rinna/japanese-wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0080
- Cer: 0.3084
- Wer: 0.999

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 77380
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Cer    | Wer   |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-----:|
| 3.5786        | 1.0   | 19348  | 3.4423          | 0.5827 | 1.0   |
| 1.5754        | 2.0   | 38696  | 2.3013          | 0.5027 | 1.0   |
| 1.2976        | 3.0   | 58044  | 2.1926          | 0.4518 | 1.0   |
| 1.1784        | 4.0   | 77392  | 1.8865          | 0.4352 | 1.0   |
| 1.1072        | 5.0   | 96740  | 1.8018          | 0.4392 | 1.0   |
| 1.0466        | 6.0   | 116088 | 1.5333          | 0.4289 | 1.0   |
| 0.9887        | 7.0   | 135436 | 1.4297          | 0.4036 | 1.0   |
| 0.9497        | 8.0   | 154784 | 1.5539          | 0.4024 | 1.0   |
| 0.9075        | 9.0   | 174132 | 1.6214          | 0.4160 | 1.0   |
| 0.8721        | 10.0  | 193480 | 1.3556          | 0.3964 | 1.0   |
| 0.8398        | 11.0  | 212828 | 1.1912          | 0.3772 | 1.0   |
| 0.8069        | 12.0  | 232176 | 1.1510          | 0.3529 | 0.999 |
| 0.7788        | 13.0  | 251524 | 1.0752          | 0.3399 | 0.999 |
| 0.7477        | 14.0  | 270872 | 1.0926          | 0.3373 | 0.999 |
| 0.7198        | 15.0  | 290220 | 0.9936          | 0.3101 | 0.999 |
| 0.7028        | 16.0  | 309568 | 1.0239          | 0.3123 | 0.999 |
| 0.6806        | 17.0  | 328916 | 1.0006          | 0.3081 | 0.999 |
| 0.6733        | 18.0  | 348264 | 1.0348          | 0.3156 | 0.999 |
| 0.6709        | 19.0  | 367612 | 1.0075          | 0.3086 | 0.999 |
| 0.6651        | 20.0  | 386960 | 1.0080          | 0.3084 | 0.999 |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1