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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- unsloth
- generated_from_trainer
model-index:
- name: l3.1-8b-ins-magiccoder
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. -->
# l3.1-8b-ins-magiccoder
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2331
## 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: 0.0001
- 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: 0.56
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4834 | 0.0130 | 2 | 1.3970 |
| 1.2584 | 0.0259 | 4 | 1.3753 |
| 1.2988 | 0.0389 | 6 | 1.3373 |
| 1.3458 | 0.0518 | 8 | 1.3058 |
| 1.2461 | 0.0648 | 10 | 1.2893 |
| 1.263 | 0.0777 | 12 | 1.2828 |
| 1.2758 | 0.0907 | 14 | 1.2782 |
| 1.2802 | 0.1036 | 16 | 1.2702 |
| 1.137 | 0.1166 | 18 | 1.2617 |
| 1.336 | 0.1296 | 20 | 1.2531 |
| 1.1811 | 0.1425 | 22 | 1.2466 |
| 1.1447 | 0.1555 | 24 | 1.2441 |
| 1.177 | 0.1684 | 26 | 1.2426 |
| 1.2585 | 0.1814 | 28 | 1.2404 |
| 1.1993 | 0.1943 | 30 | 1.2381 |
| 1.1566 | 0.2073 | 32 | 1.2370 |
| 1.2826 | 0.2202 | 34 | 1.2364 |
| 1.1512 | 0.2332 | 36 | 1.2356 |
| 1.1779 | 0.2462 | 38 | 1.2352 |
| 1.261 | 0.2591 | 40 | 1.2346 |
| 1.1998 | 0.2721 | 42 | 1.2341 |
| 1.1847 | 0.2850 | 44 | 1.2335 |
| 1.1266 | 0.2980 | 46 | 1.2336 |
| 1.1699 | 0.3109 | 48 | 1.2336 |
| 1.283 | 0.3239 | 50 | 1.2332 |
| 1.2469 | 0.3368 | 52 | 1.2331 |
| 1.1653 | 0.3498 | 54 | 1.2330 |
| 1.2752 | 0.3628 | 56 | 1.2332 |
| 1.2077 | 0.3757 | 58 | 1.2331 |
| 1.1729 | 0.3887 | 60 | 1.2330 |
| 1.2643 | 0.4016 | 62 | 1.2331 |
| 1.3324 | 0.4146 | 64 | 1.2331 |
| 1.2215 | 0.4275 | 66 | 1.2332 |
| 1.2623 | 0.4405 | 68 | 1.2332 |
| 1.2845 | 0.4534 | 70 | 1.2331 |
| 1.1966 | 0.4664 | 72 | 1.2331 |
| 1.2389 | 0.4794 | 74 | 1.2331 |
| 1.1957 | 0.4923 | 76 | 1.2331 |
| 1.2684 | 0.5053 | 78 | 1.2331 |
| 1.3217 | 0.5182 | 80 | 1.2331 |
| 1.3126 | 0.5312 | 82 | 1.2331 |
| 1.2146 | 0.5441 | 84 | 1.2330 |
| 1.216 | 0.5571 | 86 | 1.2331 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1 |