This model is a fine-tuned version of tsavage68/IE_M2_1000steps_1e7rate_SFT on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3782
Rewards/chosen: -0.1103
Rewards/rejected: -2.3818
Rewards/accuracies: 0.4600
Rewards/margins: 2.2716
Logps/rejected: -48.9613
Logps/chosen: -42.5731
Logits/rejected: -2.9040
Logits/chosen: -2.8424

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-07
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
0.4682	0.4	50	0.3782	-0.1103	-2.3818	0.4600	2.2716	-48.9613	-42.5731	-2.9040	-2.8424

Framework versions

Transformers 4.44.2
Pytorch 2.0.0+cu117
Datasets 3.0.0
Tokenizers 0.19.1

tsavage68/IE_M2_50steps_1e7rate_03beta_SFT

IE_M2_50steps_1e7rate_03beta_SFT

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tsavage68/
IE_M2_50steps_1e7rate_03beta_SFT