---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: iteboshi-small
  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-small

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9635
- Wer: 94.6252
- Cer: 50.3003

## 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     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:|
| 1.1451        | 1.1013  | 1000  | 1.3127          | 98.0009 | 52.9954 |
| 0.6729        | 2.2026  | 2000  | 0.9211          | 94.9364 | 36.0076 |
| 0.4087        | 3.3040  | 3000  | 0.8170          | 91.4757 | 33.0592 |
| 0.303         | 4.4053  | 4000  | 0.7996          | 95.9642 | 35.4912 |
| 0.211         | 5.5066  | 5000  | 0.7910          | 90.7685 | 39.8708 |
| 0.1389        | 6.6079  | 6000  | 0.8133          | 91.2588 | 46.3311 |
| 0.0864        | 7.7093  | 7000  | 0.8312          | 92.6638 | 39.9178 |
| 0.0729        | 8.8106  | 8000  | 0.8530          | 91.6172 | 50.7434 |
| 0.0381        | 9.9119  | 9000  | 0.8698          | 91.5700 | 47.7159 |
| 0.028         | 11.0132 | 10000 | 0.8864          | 92.1452 | 54.3756 |
| 0.0142        | 12.1145 | 11000 | 0.8988          | 93.2107 | 53.6414 |
| 0.0131        | 13.2159 | 12000 | 0.9192          | 92.8053 | 46.2153 |
| 0.0088        | 14.3172 | 13000 | 0.9230          | 93.8142 | 54.3103 |
| 0.0092        | 15.4185 | 14000 | 0.9310          | 94.0311 | 53.1192 |
| 0.0069        | 16.5198 | 15000 | 0.9370          | 93.8802 | 51.9775 |
| 0.0023        | 17.6211 | 16000 | 0.9437          | 94.2386 | 49.6876 |
| 0.0026        | 18.7225 | 17000 | 0.9495          | 94.0971 | 51.5929 |
| 0.0016        | 19.8238 | 18000 | 0.9531          | 94.1631 | 51.0942 |
| 0.0015        | 20.9251 | 19000 | 0.9608          | 94.7006 | 50.9125 |
| 0.0012        | 22.0264 | 20000 | 0.9635          | 94.6252 | 50.3003 |


### Framework versions

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