---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: iteboshi-tiny
  results: []
---

<!-- 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. -->

# iteboshi-tiny

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9326
- Wer: 115.2570
- Cer: 50.1238

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer      | Cer      |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|:--------:|
| 0.5915        | 1.1013  | 1000  | 0.7334          | 158.2838 | 65.0516  |
| 0.4754        | 2.2026  | 2000  | 0.6800          | 176.7751 | 66.8021  |
| 0.3484        | 3.3040  | 3000  | 0.6674          | 250.1933 | 86.5160  |
| 0.3012        | 4.4053  | 4000  | 0.6733          | 390.6648 | 143.7552 |
| 0.2416        | 5.5066  | 5000  | 0.6857          | 259.8491 | 89.0706  |
| 0.194         | 6.6079  | 6000  | 0.7101          | 197.0769 | 75.6325  |
| 0.1436        | 7.7093  | 7000  | 0.7327          | 235.4833 | 103.3691 |
| 0.135         | 8.8106  | 8000  | 0.7635          | 223.1306 | 96.6303  |
| 0.0854        | 9.9119  | 9000  | 0.7848          | 235.6624 | 96.6693  |
| 0.062         | 11.0132 | 10000 | 0.8102          | 199.8114 | 83.9929  |
| 0.0299        | 12.1145 | 11000 | 0.8364          | 177.0486 | 102.8057 |
| 0.0254        | 13.2159 | 12000 | 0.8552          | 176.0868 | 85.5468  |
| 0.0196        | 14.3172 | 13000 | 0.8671          | 126.2801 | 60.4427  |
| 0.0136        | 15.4185 | 14000 | 0.8813          | 177.9727 | 73.2561  |
| 0.0102        | 16.5198 | 15000 | 0.8930          | 142.6968 | 57.3544  |
| 0.0079        | 17.6211 | 16000 | 0.9064          | 132.6167 | 59.8736  |
| 0.0074        | 18.7225 | 17000 | 0.9160          | 125.6011 | 55.9026  |
| 0.0053        | 19.8238 | 18000 | 0.9245          | 116.0113 | 50.1628  |
| 0.0052        | 20.9251 | 19000 | 0.9299          | 115.0872 | 47.7766  |
| 0.0043        | 22.0264 | 20000 | 0.9326          | 115.2570 | 50.1238  |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1