MedQA_L3_250steps_1e6rate_05beat_CSFTDPO

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5035
• Rewards/chosen: -0.9245
• Rewards/rejected: -2.5465
• Rewards/accuracies: 0.7626
• Rewards/margins: 1.6220
• Logps/rejected: -26.4095
• Logps/chosen: -20.0716
• Logits/rejected: -0.9727
• Logits/chosen: -0.9715

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: 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
0.7075	0.0489	50	0.6367	0.2363	0.0705	0.6571	0.1658	-21.1755	-17.7501	-0.9379	-0.9373
0.6451	0.0977	100	0.6114	-0.8886	-1.7629	0.6923	0.8743	-24.8423	-19.9998	-0.9999	-0.9992
0.7372	0.1466	150	0.5770	-1.9159	-3.2984	0.7253	1.3825	-27.9133	-22.0544	-0.9880	-0.9871
0.4401	0.1954	200	0.5109	-0.9476	-2.5465	0.7516	1.5989	-26.4095	-20.1178	-0.9750	-0.9738
0.6774	0.2443	250	0.5035	-0.9245	-2.5465	0.7626	1.6220	-26.4095	-20.0716	-0.9727	-0.9715

Framework versions

• Transformers 4.41.0
• Pytorch 2.0.0+cu117
• Datasets 2.19.1
• Tokenizers 0.19.1