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positive-chosen-llama-chat-without-none
Evan-Lin/positive-chosen-llama-chat-without-none
positive-chosen-llama-chat-without-none 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. --
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At a glance
- Library
- peft
- Access
- Public
- Created
- Jan 29, 2024
- Updated
- Feb 16, 2024
- SHA
- 5ec1e42a
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. -->
dpo-llama-chat-without-none
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.9481
- Rewards/chosen: 4.6795
- Rewards/rejected: 2.8189
- Rewards/accuracies: 0.8547
- Rewards/margins: 1.8606
- Logps/rejected: -60.8495
- Logps/chosen: -50.0326
- Logits/rejected: -0.2216
- Logits/chosen: -0.2323
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 6.3 | 0.24 | 100 | 6.1290 | 3.4767 | 3.2110 | 0.5920 | 0.2657 | -56.9286 | -62.0606 | -0.2723 | -0.2654 |
| 5.5843 | 0.48 | 200 | 5.8936 | 3.6904 | 3.2305 | 0.6520 | 0.4599 | -56.7330 | -59.9230 | 0.2517 | 0.2475 |
| 5.757 | 0.72 | 300 | 5.6694 | 3.9164 | 3.1893 | 0.7253 | 0.7271 | -57.1450 | -57.6631 | 0.3505 | 0.3418 |
| 5.5385 | 0.96 | 400 | 5.4629 | 4.1466 | 3.1351 | 0.7600 | 1.0115 | -57.6871 | -55.3611 | 0.2059 | 0.1970 |
| 5.2301 | 1.2 | 500 | 5.2891 | 4.3324 | 3.0305 | 0.7880 | 1.3020 | -58.7338 | -53.5027 | 0.1063 | 0.0968 |
| 5.0115 | 1.44 | 600 | 5.1601 | 4.4582 | 2.9458 | 0.8213 | 1.5124 | -59.5800 | -52.2452 | -0.1082 | -0.1154 |
| 4.9893 | 1.68 | 700 | 5.0431 | 4.5787 | 2.9142 | 0.8413 | 1.6645 | -59.8968 | -51.0404 | -0.1716 | -0.1829 |
| 5.0292 | 1.92 | 800 | 4.9770 | 4.6501 | 2.8827 | 0.8427 | 1.7673 | -60.2111 | -50.3266 | -0.1929 | -0.2042 |
| 4.331 | 2.16 | 900 | 4.9577 | 4.6724 | 2.8191 | 0.8480 | 1.8534 | -60.8478 | -50.1027 | -0.2005 | -0.2121 |
| 4.5481 | 2.4 | 1000 | 4.9481 | 4.6795 | 2.8189 | 0.8547 | 1.8606 | -60.8495 | -50.0326 | -0.2216 | -0.2323 |
Framework versions
- PEFT 0.8.2
- Transformers 4.36.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Library
- peft
- Created
- Jan 29, 2024
- Updated
- Feb 16, 2024