Downloads · 30 days
8
5% of all-time downloads
results
Evan-Lin/results
results is a machine learning model from Evan-Lin. 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.
should probably proofread and complete it, then remove this comment. --
All-time downloads
149
Public
Repo size
70.5 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.json88.8 MB · 78%
At a glance
- Library
- peft
- Access
- Public
- Created
- Jan 22, 2024
- Updated
- Jan 22, 2024
- SHA
- 49b2d744
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. -->
results
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0483
- Rewards/chosen: 0.8443
- Rewards/rejected: -4.9894
- Rewards/accuracies: 0.9864
- Rewards/margins: 5.8337
- Logps/rejected: -163.0178
- Logps/chosen: -85.8088
- Logits/rejected: -1.0144
- Logits/chosen: -0.8703
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: 0.0005
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.5635 | 0.24 | 100 | 0.5460 | 0.2168 | -0.4663 | 0.7367 | 0.6831 | -117.7869 | -92.0844 | -1.3150 | -1.2411 |
| 0.3836 | 0.47 | 200 | 0.3582 | 0.1507 | -1.4599 | 0.8494 | 1.6106 | -127.7231 | -92.7453 | -0.6842 | -0.5917 |
| 0.2525 | 0.71 | 300 | 0.2509 | 0.6325 | -1.7217 | 0.9095 | 2.3542 | -130.3404 | -87.9269 | -0.7855 | -0.6860 |
| 0.1625 | 0.94 | 400 | 0.1711 | 0.6613 | -2.8054 | 0.9357 | 3.4667 | -141.1781 | -87.6390 | -0.7853 | -0.6836 |
| 0.0695 | 1.18 | 500 | 0.1215 | 0.6443 | -3.7903 | 0.9589 | 4.4347 | -151.0267 | -87.8085 | -0.8915 | -0.7635 |
| 0.0448 | 1.42 | 600 | 0.0905 | 1.0284 | -4.1415 | 0.9698 | 5.1699 | -154.5387 | -83.9677 | -0.9632 | -0.8182 |
| 0.0515 | 1.65 | 700 | 0.0760 | 1.1233 | -3.6423 | 0.9758 | 4.7656 | -149.5469 | -83.0189 | -0.9748 | -0.8504 |
| 0.0396 | 1.89 | 800 | 0.0542 | 0.7363 | -4.9101 | 0.9864 | 5.6464 | -162.2247 | -86.8886 | -1.0377 | -0.8963 |
| 0.0099 | 2.13 | 900 | 0.0486 | 0.8344 | -4.9605 | 0.9864 | 5.7949 | -162.7287 | -85.9078 | -1.0199 | -0.8760 |
| 0.0107 | 2.36 | 1000 | 0.0483 | 0.8443 | -4.9894 | 0.9864 | 5.8337 | -163.0178 | -85.8088 | -1.0144 | -0.8703 |
Framework versions
- PEFT 0.7.1
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- peft
- Created
- Jan 22, 2024
- Updated
- Jan 22, 2024