This model is a fine-tuned version of tsavage68/UTI_M2_1000steps_1e7rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5476
Rewards/chosen: -0.0191
Rewards/rejected: -2.0342
Rewards/accuracies: 0.2100
Rewards/margins: 2.0151
Logps/rejected: -29.7161
Logps/chosen: -4.7332
Logits/rejected: -2.5508
Logits/chosen: -2.5517

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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6238	0.3333	25	0.6989	0.0094	-1.0339	0.1900	1.0433	-19.7134	-4.4489	-2.5742	-2.5732
0.6671	0.6667	50	0.5476	-0.0191	-2.0342	0.2100	2.0151	-29.7161	-4.7332	-2.5508	-2.5517

Framework versions

Transformers 4.41.2
Pytorch 2.0.0+cu117
Datasets 2.19.2
Tokenizers 0.19.1

tsavage68/UTI2_M2_50steps_1e6rate_01beta_CSFTDPO

UTI2_M2_50steps_1e6rate_01beta_CSFTDPO

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tsavage68/
UTI2_M2_50steps_1e6rate_01beta_CSFTDPO