Downloads · 30 days
0
V0316MP2
Litzy619/V0316MP2
V0316MP2 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. --
Access
Public
Updated Mar 20, 2024
Parameters
2.8B
5.7 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors5.7 GB · 100%
Parameter types
How the weights are stored.
F162.8B · 99%
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. -->
V0316MP2
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0962
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- 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: 20
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5399 | 0.09 | 10 | 2.3219 |
| 2.1738 | 0.17 | 20 | 1.8070 |
| 1.6126 | 0.26 | 30 | 1.2246 |
| 1.1047 | 0.34 | 40 | 0.7910 |
| 0.6789 | 0.43 | 50 | 0.3123 |
| 0.3195 | 0.51 | 60 | 0.1536 |
| 0.2157 | 0.6 | 70 | 0.1208 |
| 0.1791 | 0.68 | 80 | 0.1139 |
| 0.16 | 0.77 | 90 | 0.1100 |
| 0.1628 | 0.85 | 100 | 0.1076 |
| 0.1556 | 0.94 | 110 | 0.1066 |
| 0.1509 | 1.02 | 120 | 0.1057 |
| 0.1575 | 1.11 | 130 | 0.1040 |
| 0.1502 | 1.19 | 140 | 0.1038 |
| 0.148 | 1.28 | 150 | 0.1024 |
| 0.1478 | 1.37 | 160 | 0.1019 |
| 0.1469 | 1.45 | 170 | 0.1015 |
| 0.1339 | 1.54 | 180 | 0.1008 |
| 0.1433 | 1.62 | 190 | 0.1002 |
| 0.1408 | 1.71 | 200 | 0.0993 |
| 0.1391 | 1.79 | 210 | 0.0987 |
| 0.1411 | 1.88 | 220 | 0.0980 |
| 0.1345 | 1.96 | 230 | 0.0975 |
| 0.1422 | 2.05 | 240 | 0.0968 |
| 0.1374 | 2.13 | 250 | 0.0970 |
| 0.1341 | 2.22 | 260 | 0.0970 |
| 0.1346 | 2.3 | 270 | 0.0968 |
| 0.1412 | 2.39 | 280 | 0.0966 |
| 0.1339 | 2.47 | 290 | 0.0959 |
| 0.1395 | 2.56 | 300 | 0.0961 |
| 0.1376 | 2.65 | 310 | 0.0961 |
| 0.1384 | 2.73 | 320 | 0.0960 |
| 0.1374 | 2.82 | 330 | 0.0958 |
| 0.1295 | 2.9 | 340 | 0.0959 |
| 0.1298 | 2.99 | 350 | 0.0962 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- mit
- Created
- Mar 19, 2024
- Updated
- Mar 20, 2024