phi-2-distilabeled-intel-orca-dpo
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: 0.3007
- Rewards/chosen: 0.0679
- Rewards/rejected: -1.3058
- Rewards/accuracies: 0.9265
- Rewards/margins: 1.3737
- Logps/rejected: -265.9995
- Logps/chosen: -117.6325
- Logits/rejected: 0.3789
- Logits/chosen: 0.3129
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
- training_steps: 100
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.6803 | 0.06 | 20 | 0.6533 | 0.0100 | -0.0741 | 0.8386 | 0.0841 | -253.6825 | -118.2115 | 0.3760 | 0.3395 |
0.5855 | 0.12 | 40 | 0.5133 | 0.0376 | -0.3927 | 0.9195 | 0.4303 | -256.8685 | -117.9349 | 0.3829 | 0.3363 |
0.452 | 0.19 | 60 | 0.3846 | 0.0620 | -0.8319 | 0.9246 | 0.8938 | -261.2602 | -117.6917 | 0.3875 | 0.3290 |
0.3538 | 0.25 | 80 | 0.3200 | 0.0716 | -1.1689 | 0.9269 | 1.2405 | -264.6308 | -117.5958 | 0.3836 | 0.3189 |
0.295 | 0.31 | 100 | 0.3007 | 0.0679 | -1.3058 | 0.9265 | 1.3737 | -265.9995 | -117.6325 | 0.3789 | 0.3129 |
Framework versions
- PEFT 0.7.1
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for davidberenstein1957/phi-2-distilabeled-intel-orca-dpo
Base model
microsoft/phi-2