This model is a fine-tuned version of tsavage68/Na_M2_1000steps_1e7_SFT on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6653
Rewards/chosen: 0.0172
Rewards/rejected: -0.0396
Rewards/accuracies: 0.9100
Rewards/margins: 0.0568
Logps/rejected: -80.3192
Logps/chosen: -47.9599
Logits/rejected: -2.5356
Logits/chosen: -2.5482

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: 300

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6929	0.2667	50	0.6931	-0.0010	-0.0014	0.5700	0.0003	-79.9371	-48.1427	-2.5355	-2.5481
0.6881	0.5333	100	0.6832	0.0062	-0.0142	0.6900	0.0204	-80.0656	-48.0704	-2.5357	-2.5482
0.67	0.8	150	0.6690	0.0151	-0.0343	0.9000	0.0494	-80.2661	-47.9813	-2.5359	-2.5485
0.6726	1.0667	200	0.6633	0.0167	-0.0444	0.9500	0.0611	-80.3677	-47.9656	-2.5356	-2.5482
0.6615	1.3333	250	0.6653	0.0172	-0.0396	0.9100	0.0568	-80.3192	-47.9599	-2.5356	-2.5482
0.667	1.6	300	0.6653	0.0172	-0.0396	0.9100	0.0568	-80.3192	-47.9599	-2.5356	-2.5482

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

tsavage68/Na_M2_300steps_1e8rate_01beta_cSFTDPO

Na_M2_300steps_1e8rate_01beta_cSFTDPO

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tsavage68/
Na_M2_300steps_1e8rate_01beta_cSFTDPO