tsavage68/Summary4500_M2_400steps_1e8rate_01beta_CSFTDPO

Hyponatremia_M2_400steps_1e8rate_01beta_CSFTDPO

This model is a fine-tuned version of tsavage68/Summary4500_M2_200steps_1e7rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6838
• Rewards/chosen: 0.0016
• Rewards/rejected: -0.0180
• Rewards/accuracies: 0.6400
• Rewards/margins: 0.0196
• Logps/rejected: -152.9099
• Logps/chosen: -93.7234
• Logits/rejected: -2.3527
• Logits/chosen: -2.3052

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-08
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6837	0.0112	50	0.6927	-0.0020	-0.0036	0.4960	0.0017	-152.7662	-93.7594	-2.3523	-2.3049
0.6845	0.0224	100	0.6912	0.0015	-0.0032	0.5580	0.0047	-152.7614	-93.7247	-2.3530	-2.3055
0.693	0.0336	150	0.6873	-0.0010	-0.0136	0.6160	0.0126	-152.8659	-93.7498	-2.3518	-2.3044
0.6856	0.0448	200	0.6873	-0.0005	-0.0133	0.5920	0.0128	-152.8629	-93.7448	-2.3518	-2.3044
0.6791	0.0559	250	0.6863	-0.0009	-0.0155	0.5820	0.0146	-152.8851	-93.7492	-2.3522	-2.3047
0.6961	0.0671	300	0.6838	-0.0005	-0.0202	0.6320	0.0196	-152.9316	-93.7453	-2.3517	-2.3043
0.6984	0.0783	350	0.6840	0.0016	-0.0177	0.6380	0.0192	-152.9066	-93.7241	-2.3527	-2.3052
0.6724	0.0895	400	0.6838	0.0016	-0.0180	0.6400	0.0196	-152.9099	-93.7234	-2.3527	-2.3052

Framework versions

• Transformers 4.42.4
• Pytorch 2.0.0+cu117
• Datasets 2.20.0
• Tokenizers 0.19.1