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llama3-70B-lora-pretrain_v2
ytcheng/llama3-70B-lora-pretrain_v2
llama3-70B-lora-pretrain_v2 is a machine learning model from ytcheng. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as llama3.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- llama3
- Access
- Public
- Created
- May 20, 2024
- Updated
- May 21, 2024
- SHA
- ac59fb7d
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
llama3-70B-lora-pretrain_v2
This model is a fine-tuned version of meta-llama/Meta-Llama-3-70B-Instruct on the sm_artile dataset. It achieves the following results on the evaluation set:
- Loss: 1.9382
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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6995 | 0.0939 | 100 | 2.6305 |
| 2.4199 | 0.1877 | 200 | 2.3979 |
| 2.2722 | 0.2816 | 300 | 2.2180 |
| 2.0762 | 0.3754 | 400 | 2.1251 |
| 1.9652 | 0.4693 | 500 | 2.0858 |
| 2.1893 | 0.5631 | 600 | 2.0629 |
| 2.0153 | 0.6570 | 700 | 2.0473 |
| 1.9911 | 0.7508 | 800 | 2.0318 |
| 2.1041 | 0.8447 | 900 | 2.0198 |
| 2.0488 | 0.9385 | 1000 | 2.0117 |
| 1.897 | 1.0324 | 1100 | 2.0018 |
| 2.0298 | 1.1262 | 1200 | 1.9952 |
| 2.0989 | 1.2201 | 1300 | 1.9890 |
| 1.8695 | 1.3139 | 1400 | 1.9838 |
| 2.1573 | 1.4078 | 1500 | 1.9764 |
| 2.0183 | 1.5016 | 1600 | 1.9713 |
| 1.9229 | 1.5955 | 1700 | 1.9672 |
| 1.9732 | 1.6893 | 1800 | 1.9617 |
| 1.6835 | 1.7832 | 1900 | 1.9574 |
| 1.9874 | 1.8771 | 2000 | 1.9539 |
| 1.7607 | 1.9709 | 2100 | 1.9512 |
| 1.9459 | 2.0648 | 2200 | 1.9480 |
| 1.7611 | 2.1586 | 2300 | 1.9463 |
| 1.8491 | 2.2525 | 2400 | 1.9441 |
| 1.9121 | 2.3463 | 2500 | 1.9427 |
| 1.8849 | 2.4402 | 2600 | 1.9413 |
| 2.0679 | 2.5340 | 2700 | 1.9400 |
| 1.9908 | 2.6279 | 2800 | 1.9394 |
| 1.9557 | 2.7217 | 2900 | 1.9388 |
| 1.9627 | 2.8156 | 3000 | 1.9384 |
| 1.8339 | 2.9094 | 3100 | 1.9383 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.19.1
- Library
- peft
- License
- llama3
- Created
- May 20, 2024
- Updated
- May 21, 2024