Downloads · 30 days
0
V0417MADP13
Litzy619/V0417MADP13
V0417MADP13 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 Apr 19, 2024
Parameters
2.9B
6.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors5.9 GB · 91%
Parameter types
How the weights are stored.
F162.8B · 97%
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. -->
V0417MADP13
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: 0.0634
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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.3575 | 0.09 | 10 | 1.5142 |
| 0.886 | 0.18 | 20 | 0.1389 |
| 0.1514 | 0.27 | 30 | 0.1095 |
| 0.1181 | 0.36 | 40 | 0.0951 |
| 0.1013 | 0.45 | 50 | 0.0856 |
| 0.0968 | 0.54 | 60 | 0.0774 |
| 0.0867 | 0.63 | 70 | 0.0742 |
| 0.0864 | 0.73 | 80 | 0.0717 |
| 0.0809 | 0.82 | 90 | 0.0708 |
| 0.0806 | 0.91 | 100 | 0.0680 |
| 0.0778 | 1.0 | 110 | 0.0690 |
| 0.0705 | 1.09 | 120 | 0.0666 |
| 0.0702 | 1.18 | 130 | 0.0656 |
| 0.0676 | 1.27 | 140 | 0.0677 |
| 0.0637 | 1.36 | 150 | 0.0657 |
| 0.0721 | 1.45 | 160 | 0.0639 |
| 0.0645 | 1.54 | 170 | 0.0632 |
| 0.0692 | 1.63 | 180 | 0.0622 |
| 0.0615 | 1.72 | 190 | 0.0630 |
| 0.0707 | 1.81 | 200 | 0.0609 |
| 0.0587 | 1.9 | 210 | 0.0625 |
| 0.0606 | 1.99 | 220 | 0.0626 |
| 0.0522 | 2.08 | 230 | 0.0617 |
| 0.0544 | 2.18 | 240 | 0.0625 |
| 0.0496 | 2.27 | 250 | 0.0625 |
| 0.0532 | 2.36 | 260 | 0.0635 |
| 0.0522 | 2.45 | 270 | 0.0631 |
| 0.0492 | 2.54 | 280 | 0.0635 |
| 0.0502 | 2.63 | 290 | 0.0641 |
| 0.0521 | 2.72 | 300 | 0.0634 |
| 0.0587 | 2.81 | 310 | 0.0631 |
| 0.0512 | 2.9 | 320 | 0.0634 |
| 0.0572 | 2.99 | 330 | 0.0634 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 18, 2024
- Updated
- Apr 19, 2024