mistralit2_250_STEPS_1e7_rate_0.1_beta_DPO

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mistralit2_250_STEPS_1e7_rate_0.1_beta_DPO

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6226
• Rewards/chosen: -1.1689
• Rewards/rejected: -1.4764
• Rewards/accuracies: 0.5912
• Rewards/margins: 0.3075
• Logps/rejected: -43.3368
• Logps/chosen: -35.0753
• Logits/rejected: -2.8107
• Logits/chosen: -2.8112

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: 4
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• training_steps: 250

Training results

Framework versions

• Transformers 4.38.2
• Pytorch 2.0.0+cu117
• Datasets 2.18.0
• Tokenizers 0.15.2