---
library_name: transformers
base_model: halcyon-llm/SmolLM2-360M-japanese_patch-11000
tags:
- generated_from_trainer
datasets:
- kajuma/training_01-09_token
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [halcyon-llm/SmolLM2-360M-japanese_patch-11000](https://huggingface.co/halcyon-llm/SmolLM2-360M-japanese_patch-11000) on the kajuma/training_01-09_token dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1685

## 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: 0.003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_min_lr
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.3365        | 0.0438 | 500   | 1.3520          |
| 1.3108        | 0.0877 | 1000  | 1.3424          |
| 1.2777        | 0.1315 | 1500  | 1.3183          |
| 1.3173        | 0.1754 | 2000  | 1.2995          |
| 1.2953        | 0.2192 | 2500  | 1.2839          |
| 1.2651        | 0.2631 | 3000  | 1.2729          |
| 1.2416        | 0.3069 | 3500  | 1.2610          |
| 1.2501        | 0.3508 | 4000  | 1.2496          |
| 1.2258        | 0.3946 | 4500  | 1.2393          |
| 1.1961        | 0.4385 | 5000  | 1.2292          |
| 1.2401        | 0.4823 | 5500  | 1.2193          |
| 1.2089        | 0.5262 | 6000  | 1.2098          |
| 1.1854        | 0.5700 | 6500  | 1.2019          |
| 1.1716        | 0.6138 | 7000  | 1.1943          |
| 1.2056        | 0.6577 | 7500  | 1.1877          |
| 1.1998        | 0.7015 | 8000  | 1.1821          |
| 1.1582        | 0.7454 | 8500  | 1.1777          |
| 1.1667        | 0.7892 | 9000  | 1.1744          |
| 1.1042        | 0.8331 | 9500  | 1.1722          |
| 1.1436        | 0.8769 | 10000 | 1.1705          |
| 1.1224        | 0.9208 | 10500 | 1.1695          |
| 1.1215        | 0.9646 | 11000 | 1.1688          |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0