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Phi0503HMA11OLD
Litzy619/Phi0503HMA11OLD
Phi0503HMA11OLD is a machine learning model from Litzy619. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated May 7, 2024
Parameters
3.9B
8.4 GB on disk
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.safetensors7.9 GB · 95%
Parameter types
How the weights are stored.
BF163.8B · 98%
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. -->
Phi0503HMA11
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: 0.0603
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.2519 | 0.09 | 10 | 1.0412 |
| 0.9414 | 0.18 | 20 | 1.5076 |
| 0.5581 | 0.27 | 30 | 0.2855 |
| 0.266 | 0.36 | 40 | 0.2243 |
| 0.293 | 0.45 | 50 | 0.2186 |
| 0.2172 | 0.54 | 60 | 0.2198 |
| 0.2713 | 0.63 | 70 | 0.5296 |
| 0.2377 | 0.73 | 80 | 0.1799 |
| 0.1724 | 0.82 | 90 | 0.1653 |
| 0.1631 | 0.91 | 100 | 0.1642 |
| 0.1646 | 1.0 | 110 | 3.8048 |
| 0.8934 | 1.09 | 120 | 0.1709 |
| 0.4257 | 1.18 | 130 | 2.8704 |
| 1.0083 | 1.27 | 140 | 0.1904 |
| 0.9961 | 1.36 | 150 | 1.9067 |
| 1.3818 | 1.45 | 160 | 0.5005 |
| 0.5145 | 1.54 | 170 | 0.4971 |
| 0.3049 | 1.63 | 180 | 0.2280 |
| 0.2023 | 1.72 | 190 | 0.1794 |
| 0.1949 | 1.81 | 200 | 0.1813 |
| 0.1911 | 1.9 | 210 | 0.1823 |
| 0.1758 | 1.99 | 220 | 0.1767 |
| 0.1706 | 2.08 | 230 | 0.1721 |
| 0.1658 | 2.18 | 240 | 0.1620 |
| 0.1529 | 2.27 | 250 | 0.1515 |
| 0.1319 | 2.36 | 260 | 0.1138 |
| 0.0947 | 2.45 | 270 | 0.0714 |
| 0.068 | 2.54 | 280 | 0.0690 |
| 0.0705 | 2.63 | 290 | 0.0642 |
| 0.0653 | 2.72 | 300 | 0.0624 |
| 0.0634 | 2.81 | 310 | 0.0611 |
| 0.0632 | 2.9 | 320 | 0.0613 |
| 0.0634 | 2.99 | 330 | 0.0603 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- mit
- Created
- May 7, 2024
- Updated
- May 7, 2024