Downloads · 30 days
5
4% of all-time downloads
phi2-lora-quantized-distilabel-intel-orca-dpo-pairs
dvilasuero/phi2-lora-quantized-distilabel-intel-orca-dpo-pairs
phi2-lora-quantized-distilabel-intel-orca-dpo-pairs is a machine learning model from dvilasuero. 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
127
Public
Repo size
168 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors168 MB · 98%
At a glance
- Library
- peft
- License
- mit
- Access
- Public
- Created
- Jan 25, 2024
- Updated
- Jan 25, 2024
- SHA
- 7d98903f
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. -->
phi2-lora-quantized-distilabel-intel-orca-dpo-pairs
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: 0.5173
- Rewards/chosen: -0.0019
- Rewards/rejected: -0.7725
- Rewards/accuracies: 0.7816
- Rewards/margins: 0.7706
- Logps/rejected: -233.5226
- Logps/chosen: -214.1249
- Logits/rejected: 0.3181
- Logits/chosen: 0.2015
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6887 | 0.14 | 20 | 0.6767 | 0.0030 | -0.0331 | 0.6341 | 0.0361 | -226.1282 | -214.0752 | 0.2238 | 0.1343 |
| 0.6472 | 0.27 | 40 | 0.6171 | 0.0141 | -0.1710 | 0.7639 | 0.1852 | -227.5079 | -213.9642 | 0.2464 | 0.1508 |
| 0.5759 | 0.41 | 60 | 0.5584 | 0.0123 | -0.4023 | 0.7808 | 0.4146 | -229.8206 | -213.9829 | 0.2774 | 0.1736 |
| 0.526 | 0.54 | 80 | 0.5326 | 0.0036 | -0.5790 | 0.7816 | 0.5826 | -231.5877 | -214.0700 | 0.2983 | 0.1884 |
| 0.4963 | 0.68 | 100 | 0.5225 | 0.0020 | -0.6964 | 0.7825 | 0.6984 | -232.7611 | -214.0853 | 0.3131 | 0.1986 |
| 0.4977 | 0.81 | 120 | 0.5188 | -0.0025 | -0.7533 | 0.7816 | 0.7508 | -233.3300 | -214.1302 | 0.3162 | 0.2002 |
| 0.4818 | 0.95 | 140 | 0.5173 | -0.0019 | -0.7725 | 0.7816 | 0.7706 | -233.5226 | -214.1249 | 0.3181 | 0.2015 |
Framework versions
- PEFT 0.7.1
- Transformers 4.37.1
- Pytorch 2.1.0+cu118
- Datasets 2.16.1
- Tokenizers 0.15.1
- Library
- peft
- License
- mit
- Created
- Jan 25, 2024
- Updated
- Jan 25, 2024