Mistral_VStar_iter1 – AI Model by hbin0701 | AlphaNeural AI

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hbin0701/
Mistral_VStar_iter1

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text-generation

alignment-handbook

generated_from_trainer

HuggingFaceH4/ultrafeedback_binarized

mistralai/Mistral-7B-v0.1

autotrain_compatible

text-generation-inference

endpoints_compatible

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mistral_7b_gsm8k_ep2_1e-5_dpo

This model is a fine-tuned version of /home/hyeonbin/self_train/Verifiers/models/mistral_7b_gsm8k_ep2_1e-5_rft_round1 on the GSM8K Train Set. It achieves the following results on the evaluation set (=GSM8K Train subset):

Loss: 0.0005
Rewards/chosen: -1.7120
Rewards/rejected: -14.3548
Rewards/accuracies: 1.0
Rewards/margins: 12.6428
Logps/rejected: -1466.6733
Logps/chosen: -208.2280
Logits/rejected: -3.2168
Logits/chosen: -2.3996

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: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.014	1.0	7066	0.0005	-1.7120	-14.3548	1.0	12.6428	-1466.6733	-208.2280	-3.2168	-2.3996

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.14.6
Tokenizers 0.19.1