metadata
license: llama3
base_model: tsavage68/MedQA_L3_1000steps_1e6rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: MedQA_L3_250steps_1e7rate_05beta_CSFTDPO
results: []
MedQA_L3_250steps_1e7rate_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: 0.6492
- Rewards/chosen: 0.3403
- Rewards/rejected: 0.2334
- Rewards/accuracies: 0.6857
- Rewards/margins: 0.1070
- Logps/rejected: -33.3881
- Logps/chosen: -30.6478
- Logits/rejected: -0.7314
- Logits/chosen: -0.7307
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: 250
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.6857 | 0.0489 | 50 | 0.6947 | -0.0249 | -0.0232 | 0.4879 | -0.0018 | -33.9011 | -31.3784 | -0.7318 | -0.7312 |
0.6799 | 0.0977 | 100 | 0.6734 | 0.3881 | 0.3450 | 0.6681 | 0.0432 | -33.1649 | -30.5522 | -0.7330 | -0.7323 |
0.6286 | 0.1466 | 150 | 0.6528 | 0.4844 | 0.3866 | 0.6813 | 0.0978 | -33.0816 | -30.3598 | -0.7312 | -0.7306 |
0.6183 | 0.1954 | 200 | 0.6449 | 0.3270 | 0.2107 | 0.7143 | 0.1163 | -33.4334 | -30.6745 | -0.7312 | -0.7305 |
0.6593 | 0.2443 | 250 | 0.6492 | 0.3403 | 0.2334 | 0.6857 | 0.1070 | -33.3881 | -30.6478 | -0.7314 | -0.7307 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1