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Phi0503HMA4
Litzy619/Phi0503HMA4
Phi0503HMA4 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 4, 2024
Parameters
3.9B
16.7 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. -->
Phi0503HMA4
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: 0.0153
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: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.327 | 0.09 | 10 | 0.8261 |
| 0.4359 | 0.18 | 20 | 0.2664 |
| 0.2914 | 0.27 | 30 | 0.2506 |
| 0.2542 | 0.36 | 40 | 0.2504 |
| 0.2976 | 0.45 | 50 | 0.3288 |
| 0.3986 | 0.54 | 60 | 0.2542 |
| 2.3932 | 0.63 | 70 | 0.2711 |
| 1.9638 | 0.73 | 80 | 4.8527 |
| 3.6131 | 0.82 | 90 | 1.5739 |
| 1.1269 | 0.91 | 100 | 0.7721 |
| 0.4633 | 1.0 | 110 | 0.3521 |
| 0.2947 | 1.09 | 120 | 0.2266 |
| 0.2156 | 1.18 | 130 | 0.1790 |
| 0.2026 | 1.27 | 140 | 0.1381 |
| 0.1618 | 1.36 | 150 | 0.2401 |
| 0.1723 | 1.45 | 160 | 0.1317 |
| 0.1256 | 1.54 | 170 | 0.0996 |
| 0.1171 | 1.63 | 180 | 0.0833 |
| 0.0767 | 1.72 | 190 | 0.0579 |
| 0.0578 | 1.81 | 200 | 0.0514 |
| 0.0497 | 1.9 | 210 | 0.0414 |
| 0.0456 | 1.99 | 220 | 0.0376 |
| 0.042 | 2.08 | 230 | 0.0374 |
| 0.0435 | 2.18 | 240 | 0.0295 |
| 0.0429 | 2.27 | 250 | 0.0304 |
| 0.0396 | 2.36 | 260 | 0.0243 |
| 0.0305 | 2.45 | 270 | 0.0214 |
| 0.0277 | 2.54 | 280 | 0.0191 |
| 0.0205 | 2.63 | 290 | 0.0186 |
| 0.0228 | 2.72 | 300 | 0.0165 |
| 0.0202 | 2.81 | 310 | 0.0157 |
| 0.0236 | 2.9 | 320 | 0.0155 |
| 0.0196 | 2.99 | 330 | 0.0153 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- mit
- Created
- May 4, 2024
- Updated
- May 4, 2024