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hf_phi3_lora
satyaalmasian/hf_phi3_lora
hf_phi3_lora is a machine learning model from satyaalmasian. 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
- Jul 29, 2024
- Updated
- Aug 5, 2024
- SHA
- 708dc5e3
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. -->
hf_phi3_lora
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3171
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4828 | 0.1489 | 500 | 1.4306 |
| 1.4047 | 0.2978 | 1000 | 1.3980 |
| 1.3611 | 0.4468 | 1500 | 1.3835 |
| 1.3653 | 0.5957 | 2000 | 1.3709 |
| 1.3171 | 0.7446 | 2500 | 1.3665 |
| 1.3089 | 0.8935 | 3000 | 1.3626 |
| 1.312 | 1.0425 | 3500 | 1.3608 |
| 1.2771 | 1.1914 | 4000 | 1.3556 |
| 1.3031 | 1.3403 | 4500 | 1.3570 |
| 1.284 | 1.4892 | 5000 | 1.3508 |
| 1.2697 | 1.6382 | 5500 | 1.3477 |
| 1.2594 | 1.7871 | 6000 | 1.3453 |
| 1.254 | 1.9360 | 6500 | 1.3413 |
| 1.2652 | 2.0849 | 7000 | 1.3426 |
| 1.2529 | 2.2338 | 7500 | 1.3435 |
| 1.2544 | 2.3828 | 8000 | 1.3382 |
| 1.2511 | 2.5317 | 8500 | 1.3396 |
| 1.2548 | 2.6806 | 9000 | 1.3361 |
| 1.2483 | 2.8295 | 9500 | 1.3351 |
| 1.2442 | 2.9785 | 10000 | 1.3382 |
| 1.2426 | 3.1274 | 10500 | 1.3344 |
| 1.2265 | 3.2763 | 11000 | 1.3361 |
| 1.2255 | 3.4252 | 11500 | 1.3356 |
| 1.2269 | 3.5742 | 12000 | 1.3314 |
| 1.2396 | 3.7231 | 12500 | 1.3298 |
| 1.2303 | 3.8720 | 13000 | 1.3260 |
| 1.2254 | 4.0209 | 13500 | 1.3277 |
| 1.2277 | 4.1698 | 14000 | 1.3272 |
| 1.2295 | 4.3188 | 14500 | 1.3240 |
| 1.2375 | 4.4677 | 15000 | 1.3288 |
| 1.2038 | 4.6166 | 15500 | 1.3224 |
| 1.2322 | 4.7655 | 16000 | 1.3214 |
| 1.2015 | 4.9145 | 16500 | 1.3246 |
| 1.208 | 5.0634 | 17000 | 1.3216 |
| 1.2248 | 5.2123 | 17500 | 1.3193 |
| 1.2155 | 5.3612 | 18000 | 1.3249 |
| 1.2194 | 5.5102 | 18500 | 1.3183 |
| 1.2185 | 5.6591 | 19000 | 1.3196 |
| 1.2119 | 5.8080 | 19500 | 1.3142 |
| 1.2171 | 5.9569 | 20000 | 1.3240 |
| 1.21 | 6.1058 | 20500 | 1.3235 |
| 1.19 | 6.2548 | 21000 | 1.3171 |
Framework versions
- PEFT 0.9.0
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
- Library
- peft
- License
- mit
- Created
- Jul 29, 2024
- Updated
- Aug 5, 2024