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---
base_model: unsloth/llama-3-8b-bnb-4bit
library_name: peft
license: llama3
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B_pct_ortho
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. -->
# Meta-Llama-3-8B_pct_ortho
This model is a fine-tuned version of [unsloth/llama-3-8b-bnb-4bit](https://huggingface.co/unsloth/llama-3-8b-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2409
## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.3045 | 0.0206 | 8 | 2.2825 |
| 2.2746 | 0.0412 | 16 | 2.2479 |
| 2.2264 | 0.0618 | 24 | 2.2587 |
| 2.3001 | 0.0824 | 32 | 2.2813 |
| 2.3006 | 0.1030 | 40 | 2.2798 |
| 2.2719 | 0.1236 | 48 | 2.2780 |
| 2.2942 | 0.1442 | 56 | 2.2881 |
| 2.314 | 0.1648 | 64 | 2.2993 |
| 2.2747 | 0.1854 | 72 | 2.3101 |
| 2.3086 | 0.2060 | 80 | 2.3069 |
| 2.3318 | 0.2266 | 88 | 2.2899 |
| 2.3957 | 0.2472 | 96 | 2.3000 |
| 2.3704 | 0.2678 | 104 | 2.2998 |
| 2.3319 | 0.2884 | 112 | 2.3124 |
| 2.3908 | 0.3090 | 120 | 2.3099 |
| 2.3865 | 0.3296 | 128 | 2.3063 |
| 2.3306 | 0.3502 | 136 | 2.2947 |
| 2.326 | 0.3708 | 144 | 2.2973 |
| 2.3421 | 0.3914 | 152 | 2.2987 |
| 2.3277 | 0.4120 | 160 | 2.2820 |
| 2.3739 | 0.4326 | 168 | 2.2931 |
| 2.3157 | 0.4532 | 176 | 2.2898 |
| 2.3296 | 0.4738 | 184 | 2.2915 |
| 2.3274 | 0.4944 | 192 | 2.2818 |
| 2.3225 | 0.5150 | 200 | 2.2861 |
| 2.3181 | 0.5356 | 208 | 2.2817 |
| 2.3393 | 0.5562 | 216 | 2.2708 |
| 2.3276 | 0.5768 | 224 | 2.2763 |
| 2.3053 | 0.5974 | 232 | 2.2791 |
| 2.2739 | 0.6180 | 240 | 2.2721 |
| 2.311 | 0.6386 | 248 | 2.2749 |
| 2.3049 | 0.6592 | 256 | 2.2706 |
| 2.2615 | 0.6798 | 264 | 2.2703 |
| 2.312 | 0.7004 | 272 | 2.2633 |
| 2.3017 | 0.7210 | 280 | 2.2594 |
| 2.3066 | 0.7416 | 288 | 2.2572 |
| 2.2966 | 0.7621 | 296 | 2.2579 |
| 2.3375 | 0.7827 | 304 | 2.2461 |
| 2.2704 | 0.8033 | 312 | 2.2474 |
| 2.2512 | 0.8239 | 320 | 2.2496 |
| 2.2834 | 0.8445 | 328 | 2.2431 |
| 2.2962 | 0.8651 | 336 | 2.2452 |
| 2.3071 | 0.8857 | 344 | 2.2405 |
| 2.2739 | 0.9063 | 352 | 2.2401 |
| 2.2437 | 0.9269 | 360 | 2.2435 |
| 2.2634 | 0.9475 | 368 | 2.2417 |
| 2.3116 | 0.9681 | 376 | 2.2406 |
| 2.2995 | 0.9887 | 384 | 2.2409 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |