MedQA_L3_400steps_1e6rate_03beta_CSFTDPO – AI Model by tsavage68 | AlphaNeural AI

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tsavage68/
MedQA_L3_400steps_1e6rate_03beta_CSFTDPO

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text-generation

generated_from_trainer

tsavage68/MedQA_L3_1000steps_1e6rate_SFT

autotrain_compatible

text-generation-inference

endpoints_compatible

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MedQA_L3_400steps_1e6rate_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: 0.4906
Rewards/chosen: 3.1291
Rewards/rejected: 0.9306
Rewards/accuracies: 0.7846
Rewards/margins: 2.1985
Logps/rejected: -30.7529
Logps/chosen: -20.8982
Logits/rejected: -0.8390
Logits/chosen: -0.8370

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: 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
0.685	0.0489	50	0.6334	-0.7936	-0.9359	0.7363	0.1423	-36.9746	-33.9739	-0.7278	-0.7271
0.4052	0.0977	100	0.6106	3.7995	2.4858	0.6945	1.3137	-25.5688	-18.6634	-0.7922	-0.7909
0.5527	0.1466	150	0.5749	3.2572	1.9474	0.7319	1.3099	-27.3637	-20.4711	-0.8427	-0.8414
0.3441	0.1954	200	0.5174	2.5190	0.7455	0.7582	1.7735	-31.3700	-22.9318	-0.8395	-0.8376
0.3888	0.2443	250	0.4758	3.2338	1.3417	0.7956	1.8921	-29.3826	-20.5492	-0.8342	-0.8323
0.2873	0.2931	300	0.4927	3.0141	0.8326	0.7912	2.1815	-31.0794	-21.2815	-0.8318	-0.8298
0.4877	0.3420	350	0.4903	3.1277	0.9322	0.7824	2.1956	-30.7476	-20.9027	-0.8388	-0.8368
0.4649	0.3908	400	0.4906	3.1291	0.9306	0.7846	2.1985	-30.7529	-20.8982	-0.8390	-0.8370

Framework versions

Transformers 4.41.1
Pytorch 2.0.0+cu117
Datasets 2.19.1
Tokenizers 0.19.1