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

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8963
- Wer: 81.7162
- Cer: 22.2135

## 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     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|:-------:|
| 1.0877        | 1.1013  | 1000  | 1.2933          | 98.3781 | 54.0409 |
| 0.6047        | 2.2026  | 2000  | 0.8662          | 91.6643 | 34.1946 |
| 0.3394        | 3.3040  | 3000  | 0.7763          | 88.5997 | 34.5534 |
| 0.243         | 4.4053  | 4000  | 0.7650          | 86.5912 | 26.8098 |
| 0.1633        | 5.5066  | 5000  | 0.7654          | 88.1848 | 27.4116 |
| 0.1113        | 6.6079  | 6000  | 0.7906          | 86.4215 | 26.7640 |
| 0.0673        | 7.7093  | 7000  | 0.7989          | 84.6110 | 27.1371 |
| 0.0624        | 8.8106  | 8000  | 0.8190          | 84.6582 | 24.9533 |
| 0.0355        | 9.9119  | 9000  | 0.8439          | 84.0924 | 24.8639 |
| 0.0262        | 11.0132 | 10000 | 0.8546          | 84.7525 | 25.5190 |
| 0.0146        | 12.1145 | 11000 | 0.8571          | 83.5832 | 23.8711 |
| 0.0089        | 13.2159 | 12000 | 0.8546          | 82.8666 | 23.3656 |
| 0.0098        | 14.3172 | 13000 | 0.8761          | 83.8850 | 23.7055 |
| 0.0076        | 15.4185 | 14000 | 0.8775          | 83.1872 | 23.6654 |
| 0.0044        | 16.5198 | 15000 | 0.8781          | 83.0740 | 23.5868 |
| 0.005         | 17.6211 | 16000 | 0.8774          | 82.3102 | 22.7488 |
| 0.0026        | 18.7225 | 17000 | 0.8914          | 82.1499 | 22.5316 |
| 0.0015        | 19.8238 | 18000 | 0.8890          | 81.9896 | 22.3132 |
| 0.0011        | 20.9251 | 19000 | 0.8928          | 81.6219 | 22.2513 |
| 0.0006        | 22.0264 | 20000 | 0.8963          | 81.7162 | 22.2135 |


### Framework versions

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