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DPO_davide
mazzaqq/DPO_davide
DPO_davide is a machine learning model from mazzaqq. 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. --
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At a glance
- Library
- peft
- Access
- Public
- Created
- Feb 27, 2024
- Updated
- Feb 27, 2024
- SHA
- 49714027
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. -->
sigmoid_lr2e-05_b0.1
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1587
- Rewards/chosen: 1.0566
- Rewards/rejected: -3.7222
- Rewards/accuracies: 0.9348
- Rewards/margins: 4.7788
- Logps/rejected: -100.3634
- Logps/chosen: -68.2028
- Logits/rejected: -1.2118
- Logits/chosen: -1.1884
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1582 | 0.1 | 341 | 0.3412 | 1.4613 | -0.6760 | 0.8442 | 2.1373 | -69.9019 | -64.1564 | -0.9916 | -0.9274 |
| 0.2165 | 0.2 | 682 | 0.2655 | 1.8031 | -1.3141 | 0.8714 | 3.1172 | -76.2827 | -60.7382 | -1.0115 | -0.9525 |
| 0.0864 | 0.3 | 1023 | 0.2379 | 0.6173 | -3.1475 | 0.8877 | 3.7648 | -94.6172 | -72.5967 | -1.0623 | -1.0198 |
| 0.3192 | 0.4 | 1364 | 0.2003 | 1.3681 | -2.3819 | 0.9185 | 3.7500 | -86.9604 | -65.0880 | -1.1691 | -1.1334 |
| 0.5707 | 0.5 | 1705 | 0.1831 | 1.2028 | -3.2640 | 0.9293 | 4.4667 | -95.7812 | -66.7415 | -1.2287 | -1.1992 |
| 0.0427 | 0.6 | 2046 | 0.1718 | 1.3838 | -3.1327 | 0.9312 | 4.5166 | -94.4690 | -64.9309 | -1.1900 | -1.1566 |
| 0.1956 | 0.7 | 2387 | 0.1608 | 1.0344 | -3.7242 | 0.9366 | 4.7586 | -100.3841 | -68.4254 | -1.2044 | -1.1795 |
| 0.0319 | 0.8 | 2728 | 0.1595 | 1.0398 | -3.7445 | 0.9348 | 4.7843 | -100.5868 | -68.3711 | -1.2077 | -1.1849 |
| 0.0173 | 0.9 | 3069 | 0.1587 | 1.0566 | -3.7222 | 0.9348 | 4.7788 | -100.3634 | -68.2028 | -1.2118 | -1.1884 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- peft
- Created
- Feb 27, 2024
- Updated
- Feb 27, 2024