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---
license: llama3
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- generator
model-index:
- name: cls_alldata_llama3_v1
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. -->
# cls_alldata_llama3_v1
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4523
## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6921 | 0.0582 | 20 | 0.6831 |
| 0.5975 | 0.1164 | 40 | 0.6416 |
| 0.6107 | 0.1747 | 60 | 0.6082 |
| 0.5609 | 0.2329 | 80 | 0.5883 |
| 0.5857 | 0.2911 | 100 | 0.5761 |
| 0.5386 | 0.3493 | 120 | 0.5660 |
| 0.5176 | 0.4076 | 140 | 0.5529 |
| 0.5317 | 0.4658 | 160 | 0.5379 |
| 0.5244 | 0.5240 | 180 | 0.5292 |
| 0.5218 | 0.5822 | 200 | 0.5234 |
| 0.5003 | 0.6405 | 220 | 0.5207 |
| 0.5024 | 0.6987 | 240 | 0.5096 |
| 0.4913 | 0.7569 | 260 | 0.5062 |
| 0.5174 | 0.8151 | 280 | 0.5003 |
| 0.4675 | 0.8734 | 300 | 0.4968 |
| 0.5137 | 0.9316 | 320 | 0.4903 |
| 0.4883 | 0.9898 | 340 | 0.4869 |
| 0.3616 | 1.0480 | 360 | 0.4935 |
| 0.3713 | 1.1063 | 380 | 0.4890 |
| 0.365 | 1.1645 | 400 | 0.4856 |
| 0.3732 | 1.2227 | 420 | 0.4838 |
| 0.3717 | 1.2809 | 440 | 0.4842 |
| 0.3657 | 1.3392 | 460 | 0.4811 |
| 0.3767 | 1.3974 | 480 | 0.4762 |
| 0.3859 | 1.4556 | 500 | 0.4763 |
| 0.3773 | 1.5138 | 520 | 0.4712 |
| 0.3615 | 1.5721 | 540 | 0.4671 |
| 0.3656 | 1.6303 | 560 | 0.4666 |
| 0.3497 | 1.6885 | 580 | 0.4658 |
| 0.3818 | 1.7467 | 600 | 0.4621 |
| 0.3759 | 1.8049 | 620 | 0.4626 |
| 0.3539 | 1.8632 | 640 | 0.4551 |
| 0.3985 | 1.9214 | 660 | 0.4525 |
| 0.3668 | 1.9796 | 680 | 0.4523 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |