---
library_name: peft
base_model: Casual-Autopsy/L3-Umbral-Mind-RP-v3.0-8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 21e6f667-1b4f-43b3-9117-44b455ed8d1b
results: []
---
[
](https://github.com/axolotl-ai-cloud/axolotl)
# 21e6f667-1b4f-43b3-9117-44b455ed8d1b
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: 0.2209
## 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: 0.000211
- train_batch_size: 4
- eval_batch_size: 4
- seed: 110
- 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 | 1.6972 |
| 0.6301 | 0.0307 | 50 | 0.7841 |
| 0.5207 | 0.0613 | 100 | 0.7849 |
| 0.4508 | 0.0920 | 150 | 0.5248 |
| 0.3927 | 0.1226 | 200 | 0.5356 |
| 0.3716 | 0.1533 | 250 | 0.3826 |
| 0.3506 | 0.1839 | 300 | 0.3516 |
| 0.326 | 0.2146 | 350 | 0.2691 |
| 0.2517 | 0.2452 | 400 | 0.2358 |
| 0.2535 | 0.2759 | 450 | 0.2240 |
| 0.3353 | 0.3066 | 500 | 0.2209 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1