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