---
library_name: peft
base_model: jingyeom/seal3.1.6n_7b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 7b377ecd-7e77-465c-afcc-cba370b9c5e5
  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>

# 7b377ecd-7e77-465c-afcc-cba370b9c5e5

This model is a fine-tuned version of [jingyeom/seal3.1.6n_7b](https://huggingface.co/jingyeom/seal3.1.6n_7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8523

## 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: 0.000214
- 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        | 0.0006 | 1    | 1.9465          |
| 0.8747        | 0.0293 | 50   | 1.2186          |
| 0.8156        | 0.0586 | 100  | 1.1785          |
| 0.8325        | 0.0880 | 150  | 1.0621          |
| 0.7726        | 0.1173 | 200  | 1.0214          |
| 0.7815        | 0.1466 | 250  | 0.9988          |
| 0.8154        | 0.1759 | 300  | 0.9346          |
| 0.6438        | 0.2052 | 350  | 0.8879          |
| 0.7983        | 0.2345 | 400  | 0.8639          |
| 0.6763        | 0.2639 | 450  | 0.8545          |
| 0.7375        | 0.2932 | 500  | 0.8523          |


### Framework versions

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