|
--- |
|
base_model: unsloth/llama-3-8b |
|
library_name: peft |
|
license: llama3 |
|
tags: |
|
- unsloth |
|
- generated_from_trainer |
|
model-index: |
|
- name: Meta-Llama-3-8B_magiccoder_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_magiccoder_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: 1.2697 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 1.2592 | 0.0259 | 4 | 1.4263 | |
|
| 1.4281 | 0.0518 | 8 | 1.4063 | |
|
| 1.3795 | 0.0777 | 12 | 1.3824 | |
|
| 1.3751 | 0.1036 | 16 | 1.3937 | |
|
| 1.4053 | 0.1296 | 20 | 1.3523 | |
|
| 1.2927 | 0.1555 | 24 | 1.3474 | |
|
| 1.3619 | 0.1814 | 28 | 1.3529 | |
|
| 1.3533 | 0.2073 | 32 | 1.3629 | |
|
| 1.3627 | 0.2332 | 36 | 1.3636 | |
|
| 1.4408 | 0.2591 | 40 | 1.3531 | |
|
| 1.3744 | 0.2850 | 44 | 1.3395 | |
|
| 1.2658 | 0.3109 | 48 | 1.3364 | |
|
| 1.3364 | 0.3368 | 52 | 1.3400 | |
|
| 1.3765 | 0.3628 | 56 | 1.3391 | |
|
| 1.3427 | 0.3887 | 60 | 1.3370 | |
|
| 1.3975 | 0.4146 | 64 | 1.3329 | |
|
| 1.2595 | 0.4405 | 68 | 1.3325 | |
|
| 1.3291 | 0.4664 | 72 | 1.3312 | |
|
| 1.2702 | 0.4923 | 76 | 1.3323 | |
|
| 1.3527 | 0.5182 | 80 | 1.3213 | |
|
| 1.2799 | 0.5441 | 84 | 1.3154 | |
|
| 1.3082 | 0.5700 | 88 | 1.3099 | |
|
| 1.4042 | 0.5960 | 92 | 1.3089 | |
|
| 1.2221 | 0.6219 | 96 | 1.3048 | |
|
| 1.3079 | 0.6478 | 100 | 1.3017 | |
|
| 1.2165 | 0.6737 | 104 | 1.2970 | |
|
| 1.239 | 0.6996 | 108 | 1.2941 | |
|
| 1.2528 | 0.7255 | 112 | 1.2877 | |
|
| 1.2932 | 0.7514 | 116 | 1.2859 | |
|
| 1.2762 | 0.7773 | 120 | 1.2804 | |
|
| 1.2914 | 0.8032 | 124 | 1.2791 | |
|
| 1.2835 | 0.8291 | 128 | 1.2755 | |
|
| 1.2735 | 0.8551 | 132 | 1.2731 | |
|
| 1.2264 | 0.8810 | 136 | 1.2722 | |
|
| 1.2637 | 0.9069 | 140 | 1.2713 | |
|
| 1.2133 | 0.9328 | 144 | 1.2704 | |
|
| 1.2379 | 0.9587 | 148 | 1.2699 | |
|
| 1.2131 | 0.9846 | 152 | 1.2697 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
