Downloads · 30 days
4
5% of all-time downloads
Adapter3
dxltt1211/Adapter3
Adapter3 is a machine learning model from dxltt1211. 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. --
All-time downloads
73
Public
Repo size
35.7 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors35.7 MB · 91%
At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- Sep 29, 2024
- Updated
- Sep 29, 2024
- SHA
- a0e7fc97
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. -->
Adapter3
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: 0.2331
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8448 | 1.3289 | 100 | 0.3559 |
| 0.2539 | 2.6578 | 200 | 0.2331 |
Framework versions
- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.2.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
- Library
- peft
- License
- mit
- Created
- Sep 29, 2024
- Updated
- Sep 29, 2024