Hyponatremia_M2_400steps_1e8rate_03beta_DPO – AI Model by tsavage68 | AlphaNeural AI

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tsavage68/
Hyponatremia_M2_400steps_1e8rate_03beta_DPO

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text-generation

generated_from_trainer

tsavage68/Hyponatremia_M2_150steps_1e6rate_SFT

autotrain_compatible

text-generation-inference

endpoints_compatible

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Hyponatremia_M2_400steps_1e8rate_03beta_DPO

This model is a fine-tuned version of tsavage68/Hyponatremia_M2_150steps_1e6rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6276
Rewards/chosen: 0.0345
Rewards/rejected: -0.1027
Rewards/accuracies: 0.9600
Rewards/margins: 0.1372
Logps/rejected: -71.2238
Logps/chosen: -36.6121
Logits/rejected: -2.2455
Logits/chosen: -2.2404

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: 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: 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
0.691	0.2667	50	0.6959	0.0081	0.0125	0.4400	-0.0044	-70.8398	-36.7002	-2.2478	-2.2427
0.684	0.5333	100	0.6850	0.0066	-0.0109	0.6200	0.0175	-70.9177	-36.7050	-2.2462	-2.2410
0.6496	0.8	150	0.6433	0.0267	-0.0772	0.9000	0.1039	-71.1387	-36.6380	-2.2462	-2.2412
0.6234	1.0667	200	0.6319	0.0320	-0.0962	0.9700	0.1281	-71.2020	-36.6205	-2.2465	-2.2415
0.6262	1.3333	250	0.6336	0.0321	-0.0927	0.9500	0.1248	-71.1904	-36.6199	-2.2462	-2.2411
0.6215	1.6	300	0.6288	0.0386	-0.0965	0.9600	0.1352	-71.2033	-36.5983	-2.2455	-2.2404
0.6129	1.8667	350	0.6276	0.0345	-0.1027	0.9600	0.1372	-71.2238	-36.6121	-2.2455	-2.2404
0.6301	2.1333	400	0.6276	0.0345	-0.1027	0.9600	0.1372	-71.2238	-36.6121	-2.2455	-2.2404

Framework versions

Transformers 4.42.3
Pytorch 2.0.0+cu117
Datasets 2.20.0
Tokenizers 0.19.1