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Saahil1801/
openhermes-mistral-dpo-gptq

Name: openhermes-mistral-dpo-gptq
Availability: InStock

generated_from_trainer

TheBloke/OpenHermes-2-Mistral-7B-GPTQ

finetune

apache-2.0

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openhermes-mistral-dpo-gptq

This model is a fine-tuned version of TheBloke/OpenHermes-2-Mistral-7B-GPTQ on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6599
Rewards/chosen: 0.0397
Rewards/rejected: -0.0752
Rewards/accuracies: 0.9375
Rewards/margins: 0.1149
Logps/rejected: -164.5962
Logps/chosen: -292.6904
Logits/rejected: -2.6901
Logits/chosen: -2.3670

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: 0.0002
train_batch_size: 1
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
training_steps: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6819	0.01	10	0.6600	0.0491	-0.0050	1.0	0.0540	-163.8940	-292.5971	-2.6930	-2.3675
0.7106	0.01	20	0.6787	0.0460	0.0162	0.5625	0.0298	-163.6827	-292.6277	-2.6971	-2.3713
0.6487	0.01	30	0.6889	0.0454	-0.0002	0.8125	0.0456	-163.8460	-292.6334	-2.6960	-2.3700
0.5981	0.02	40	0.6718	0.0307	-0.0583	0.9375	0.0890	-164.4272	-292.7806	-2.6928	-2.3685
0.6573	0.03	50	0.6599	0.0397	-0.0752	0.9375	0.1149	-164.5962	-292.6904	-2.6901	-2.3670

Framework versions

Transformers 4.35.2
Pytorch 2.0.1+cu117
Datasets 2.17.0
Tokenizers 0.15.1

Saahil1801/openhermes-mistral-dpo-gptq

openhermes-mistral-dpo-gptq

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Saahil1801/
openhermes-mistral-dpo-gptq