metadata
license: llama3
base_model: tsavage68/MedQA_L3_1000steps_1e6rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: MedQA_L3_350steps_1e7rate_03beta_CSFTDPO
results: []
MedQA_L3_350steps_1e7rate_03beta_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: 0.6516
- Rewards/chosen: 0.2738
- Rewards/rejected: 0.1790
- Rewards/accuracies: 0.7099
- Rewards/margins: 0.0948
- Logps/rejected: -33.2582
- Logps/chosen: -30.4158
- Logits/rejected: -0.7313
- Logits/chosen: -0.7305
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-07
- 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: 350
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6925 | 0.0489 | 50 | 0.6930 | -0.0016 | -0.0023 | 0.5011 | 0.0007 | -33.8624 | -31.3338 | -0.7320 | -0.7314 |
| 0.6841 | 0.0977 | 100 | 0.6807 | 0.2459 | 0.2195 | 0.6549 | 0.0264 | -33.1233 | -30.5088 | -0.7330 | -0.7323 |
| 0.6524 | 0.1466 | 150 | 0.6658 | 0.3522 | 0.2898 | 0.6703 | 0.0624 | -32.8887 | -30.1544 | -0.7315 | -0.7308 |
| 0.631 | 0.1954 | 200 | 0.6545 | 0.1829 | 0.0948 | 0.6923 | 0.0881 | -33.5389 | -30.7188 | -0.7310 | -0.7303 |
| 0.6675 | 0.2443 | 250 | 0.6520 | 0.2481 | 0.1544 | 0.7121 | 0.0938 | -33.3403 | -30.5014 | -0.7309 | -0.7301 |
| 0.6479 | 0.2931 | 300 | 0.6509 | 0.2738 | 0.1773 | 0.7099 | 0.0966 | -33.2640 | -30.4157 | -0.7310 | -0.7303 |
| 0.6583 | 0.3420 | 350 | 0.6516 | 0.2738 | 0.1790 | 0.7099 | 0.0948 | -33.2582 | -30.4158 | -0.7313 | -0.7305 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1