---
library_name: peft
license: apache-2.0
base_model: unsloth/SmolLM2-1.7B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: bd66b391-b975-48ac-b2fa-1517e14ff4ad
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# bd66b391-b975-48ac-b2fa-1517e14ff4ad

This model is a fine-tuned version of [unsloth/SmolLM2-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM2-1.7B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5615

## 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: 0.000206
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0000 | 1    | 2.5411          |
| 2.031         | 0.0010 | 50   | 2.0144          |
| 1.8963        | 0.0020 | 100  | 1.8420          |
| 1.7379        | 0.0029 | 150  | 1.7665          |
| 1.6386        | 0.0039 | 200  | 1.7132          |
| 1.6857        | 0.0049 | 250  | 1.6582          |
| 1.6102        | 0.0059 | 300  | 1.6215          |
| 1.6331        | 0.0069 | 350  | 1.5961          |
| 1.5731        | 0.0078 | 400  | 1.5721          |
| 1.5927        | 0.0088 | 450  | 1.5630          |
| 1.574         | 0.0098 | 500  | 1.5615          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1