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llama3-8b-instruct-qlora-medium
nrishabh/llama3-8b-instruct-qlora-medium
llama3-8b-instruct-qlora-medium is a machine learning model from nrishabh. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- May 13, 2024
- Updated
- May 13, 2024
- SHA
- 96659057
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. -->
llama3-8b-instruct-qlora-medium
This model is a fine-tuned version of LoftQ/Meta-Llama-3-8B-Instruct-4bit-64rank on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7329
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2884 | 1.0 | 105 | 1.2658 |
| 2.0727 | 2.0 | 210 | 1.0205 |
| 1.9709 | 3.0 | 315 | 0.9518 |
| 1.8768 | 4.0 | 420 | 0.9206 |
| 1.7711 | 5.0 | 525 | 0.8761 |
| 1.6379 | 6.0 | 630 | 0.8487 |
| 1.4834 | 7.0 | 735 | 0.8200 |
| 1.3144 | 8.0 | 840 | 0.8076 |
| 1.1514 | 9.0 | 945 | 0.7972 |
| 1.0148 | 10.0 | 1050 | 0.7865 |
| 0.8944 | 11.0 | 1155 | 0.7846 |
| 0.7844 | 12.0 | 1260 | 0.7767 |
| 0.699 | 13.0 | 1365 | 0.7688 |
| 0.6215 | 14.0 | 1470 | 0.7631 |
| 0.5602 | 15.0 | 1575 | 0.7584 |
| 0.503 | 16.0 | 1680 | 0.7548 |
| 0.4597 | 17.0 | 1785 | 0.7514 |
| 0.4226 | 18.0 | 1890 | 0.7484 |
| 0.3903 | 19.0 | 1995 | 0.7441 |
| 0.3646 | 20.0 | 2100 | 0.7390 |
| 0.3407 | 21.0 | 2205 | 0.7385 |
| 0.3237 | 22.0 | 2310 | 0.7357 |
| 0.3108 | 23.0 | 2415 | 0.7343 |
| 0.2999 | 24.0 | 2520 | 0.7337 |
| 0.2917 | 25.0 | 2625 | 0.7333 |
| 0.2868 | 26.0 | 2730 | 0.7324 |
| 0.2815 | 27.0 | 2835 | 0.7327 |
| 0.28 | 28.0 | 2940 | 0.7315 |
| 0.2785 | 29.0 | 3045 | 0.7322 |
| 0.2791 | 30.0 | 3150 | 0.7329 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
- Library
- peft
- License
- mit
- Created
- May 13, 2024
- Updated
- May 13, 2024