Mistral-7B-Instruct-v0.2-MI-2e-5

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

• Loss: 1.5846
• Rewards/chosen: -0.8695
• Rewards/rejected: -0.9117
• Rewards/accuracies: 0.5559
• Rewards/margins: 0.0422
• Logps/rejected: -0.9117
• Logps/chosen: -0.8695
• Logits/rejected: -2.8388
• Logits/chosen: -2.8404

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: 2e-05
• train_batch_size: 2
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 16
• total_train_batch_size: 128
• total_eval_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• 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
1.5218	0.8573	400	1.5846	-0.8695	-0.9117	0.5559	0.0422	-0.9117	-0.8695	-2.8388	-2.8404

Framework versions

• Transformers 4.42.0
• Pytorch 2.1.2+cu121
• Datasets 2.14.6
• Tokenizers 0.19.1