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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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- llama-factory |
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- lora |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-70B-Instruct |
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model-index: |
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- name: llama3-70B-lora-pretrain_v2 |
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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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# llama3-70B-lora-pretrain_v2 |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct) on the sm_artile dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9382 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 2 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 3.0 |
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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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| 2.6995 | 0.0939 | 100 | 2.6305 | |
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| 2.4199 | 0.1877 | 200 | 2.3979 | |
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| 2.2722 | 0.2816 | 300 | 2.2180 | |
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| 2.0762 | 0.3754 | 400 | 2.1251 | |
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| 1.9652 | 0.4693 | 500 | 2.0858 | |
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| 2.1893 | 0.5631 | 600 | 2.0629 | |
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| 2.0153 | 0.6570 | 700 | 2.0473 | |
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| 1.9911 | 0.7508 | 800 | 2.0318 | |
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| 2.1041 | 0.8447 | 900 | 2.0198 | |
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| 2.0488 | 0.9385 | 1000 | 2.0117 | |
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| 1.897 | 1.0324 | 1100 | 2.0018 | |
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| 2.0298 | 1.1262 | 1200 | 1.9952 | |
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| 2.0989 | 1.2201 | 1300 | 1.9890 | |
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| 1.8695 | 1.3139 | 1400 | 1.9838 | |
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| 2.1573 | 1.4078 | 1500 | 1.9764 | |
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| 2.0183 | 1.5016 | 1600 | 1.9713 | |
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| 1.9229 | 1.5955 | 1700 | 1.9672 | |
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| 1.9732 | 1.6893 | 1800 | 1.9617 | |
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| 1.6835 | 1.7832 | 1900 | 1.9574 | |
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| 1.9874 | 1.8771 | 2000 | 1.9539 | |
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| 1.7607 | 1.9709 | 2100 | 1.9512 | |
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| 1.9459 | 2.0648 | 2200 | 1.9480 | |
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| 1.7611 | 2.1586 | 2300 | 1.9463 | |
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| 1.8491 | 2.2525 | 2400 | 1.9441 | |
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| 1.9121 | 2.3463 | 2500 | 1.9427 | |
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| 1.8849 | 2.4402 | 2600 | 1.9413 | |
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| 2.0679 | 2.5340 | 2700 | 1.9400 | |
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| 1.9908 | 2.6279 | 2800 | 1.9394 | |
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| 1.9557 | 2.7217 | 2900 | 1.9388 | |
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| 1.9627 | 2.8156 | 3000 | 1.9384 | |
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| 1.8339 | 2.9094 | 3100 | 1.9383 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
