---
library_name: peft
base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: acf64dce-cea8-4814-a6b7-8431a0af1247
  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>

# acf64dce-cea8-4814-a6b7-8431a0af1247

This model is a fine-tuned version of [Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B](https://huggingface.co/Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2162

## 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: 0.000203
- train_batch_size: 4
- eval_batch_size: 4
- seed: 30
- 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    | 1.6953          |
| 0.5842        | 0.0307 | 50   | 0.7501          |
| 0.579         | 0.0613 | 100  | 0.7242          |
| 0.5286        | 0.0920 | 150  | 0.5108          |
| 0.4783        | 0.1226 | 200  | 0.4689          |
| 0.345         | 0.1533 | 250  | 0.4471          |
| 0.3257        | 0.1839 | 300  | 0.3584          |
| 0.3528        | 0.2146 | 350  | 0.2692          |
| 0.2959        | 0.2452 | 400  | 0.2352          |
| 0.3381        | 0.2759 | 450  | 0.2182          |
| 0.2557        | 0.3066 | 500  | 0.2162          |


### Framework versions

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