MedQA_L3_300steps_1e6rate_05beta_CSFTDPO
This model is a fine-tuned version of tsavage68/MedQA_L3_1000steps_1e6rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5731
- Rewards/chosen: 5.8136
- Rewards/rejected: 3.5872
- Rewards/accuracies: 0.7692
- Rewards/margins: 2.2264
- Logps/rejected: -26.6804
- Logps/chosen: -19.7013
- Logits/rejected: -0.8355
- Logits/chosen: -0.8339
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-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 300
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.6909 | 0.0489 | 50 | 0.6059 | -0.4307 | -0.6542 | 0.7538 | 0.2235 | -35.1631 | -32.1898 | -0.7254 | -0.7246 |
0.4343 | 0.0977 | 100 | 0.7202 | 6.9486 | 5.2431 | 0.6989 | 1.7054 | -23.3686 | -17.4314 | -0.7816 | -0.7804 |
0.6114 | 0.1466 | 150 | 0.6428 | 3.8385 | 1.9433 | 0.7407 | 1.8951 | -29.9682 | -23.6516 | -0.8244 | -0.8232 |
0.3522 | 0.1954 | 200 | 0.5948 | 5.1038 | 2.7837 | 0.7604 | 2.3201 | -28.2874 | -21.1208 | -0.8383 | -0.8367 |
0.3837 | 0.2443 | 250 | 0.5746 | 5.7825 | 3.5643 | 0.7692 | 2.2182 | -26.7263 | -19.7636 | -0.8356 | -0.8340 |
0.3658 | 0.2931 | 300 | 0.5731 | 5.8136 | 3.5872 | 0.7692 | 2.2264 | -26.6804 | -19.7013 | -0.8355 | -0.8339 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for tsavage68/MedQA_L3_300steps_1e6rate_05beta_CSFTDPO
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Finetuned
tsavage68/MedQA_L3_1000steps_1e6rate_SFT
Finetuned
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