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---
base_model: unsloth/llama-3-8b
library_name: peft
license: llama3
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B_pct_default
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_default
This model is a fine-tuned version of [unsloth/llama-3-8b](https://huggingface.co/unsloth/llama-3-8b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1916
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.2535 | 0.0206 | 8 | 2.2735 |
| 2.2839 | 0.0412 | 16 | 2.2722 |
| 2.2318 | 0.0618 | 24 | 2.2795 |
| 2.3022 | 0.0824 | 32 | 2.2721 |
| 2.2843 | 0.1030 | 40 | 2.2608 |
| 2.2433 | 0.1236 | 48 | 2.2513 |
| 2.2617 | 0.1442 | 56 | 2.2632 |
| 2.2962 | 0.1648 | 64 | 2.2767 |
| 2.2573 | 0.1854 | 72 | 2.2800 |
| 2.2856 | 0.2060 | 80 | 2.2750 |
| 2.3158 | 0.2266 | 88 | 2.2799 |
| 2.3622 | 0.2472 | 96 | 2.2860 |
| 2.357 | 0.2678 | 104 | 2.2901 |
| 2.3124 | 0.2884 | 112 | 2.2985 |
| 2.3646 | 0.3090 | 120 | 2.2943 |
| 2.3591 | 0.3296 | 128 | 2.2891 |
| 2.3085 | 0.3502 | 136 | 2.2923 |
| 2.3054 | 0.3708 | 144 | 2.2878 |
| 2.3203 | 0.3914 | 152 | 2.2829 |
| 2.2995 | 0.4120 | 160 | 2.2783 |
| 2.356 | 0.4326 | 168 | 2.2759 |
| 2.2942 | 0.4532 | 176 | 2.2720 |
| 2.2987 | 0.4738 | 184 | 2.2650 |
| 2.3025 | 0.4944 | 192 | 2.2645 |
| 2.294 | 0.5150 | 200 | 2.2624 |
| 2.2959 | 0.5356 | 208 | 2.2678 |
| 2.3074 | 0.5562 | 216 | 2.2525 |
| 2.2862 | 0.5768 | 224 | 2.2530 |
| 2.2745 | 0.5974 | 232 | 2.2494 |
| 2.2422 | 0.6180 | 240 | 2.2398 |
| 2.275 | 0.6386 | 248 | 2.2399 |
| 2.2632 | 0.6592 | 256 | 2.2398 |
| 2.2198 | 0.6798 | 264 | 2.2288 |
| 2.2732 | 0.7004 | 272 | 2.2233 |
| 2.2576 | 0.7210 | 280 | 2.2178 |
| 2.2606 | 0.7416 | 288 | 2.2098 |
| 2.2559 | 0.7621 | 296 | 2.2151 |
| 2.2852 | 0.7827 | 304 | 2.2048 |
| 2.2252 | 0.8033 | 312 | 2.2026 |
| 2.2024 | 0.8239 | 320 | 2.2029 |
| 2.2339 | 0.8445 | 328 | 2.1969 |
| 2.2468 | 0.8651 | 336 | 2.1979 |
| 2.2582 | 0.8857 | 344 | 2.1932 |
| 2.223 | 0.9063 | 352 | 2.1925 |
| 2.1887 | 0.9269 | 360 | 2.1937 |
| 2.218 | 0.9475 | 368 | 2.1924 |
| 2.258 | 0.9681 | 376 | 2.1917 |
| 2.2479 | 0.9887 | 384 | 2.1916 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |