---
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-360M
tags:
- generated_from_trainer
datasets:
- kajuma/training_01-09_patch
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 [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M) on the kajuma/training_01-09_patch dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1002

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 3.584         | 0.0878 | 1000  | 0.1139          |
| 3.4937        | 0.1755 | 2000  | 0.1080          |
| 3.3486        | 0.2633 | 3000  | 0.1059          |
| 3.4019        | 0.3511 | 4000  | 0.1044          |
| 3.2915        | 0.4388 | 5000  | 0.1033          |
| 3.2729        | 0.5266 | 6000  | 0.1023          |
| 3.2451        | 0.6144 | 7000  | 0.1015          |
| 3.2339        | 0.7022 | 8000  | 0.1009          |
| 3.2383        | 0.7899 | 9000  | 0.1005          |
| 3.2441        | 0.8777 | 10000 | 0.1003          |
| 3.2744        | 0.9655 | 11000 | 0.1002          |


### Framework versions

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