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metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.2
tags:
  - alignment_handbook-handbook
  - generated_from_trainer
datasets:
  - princeton-nlp/mistral-instruct-ultrafeedback
model-index:
  - name: Mistral-7B-Instruct-v0.2-MI-6e-7
    results: []

Visualize in Weights & Biases

Mistral-7B-Instruct-v0.2-MI-6e-7

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: 1.5201
  • Rewards/chosen: -0.5693
  • Rewards/rejected: -0.6258
  • Rewards/accuracies: 0.5691
  • Rewards/margins: 0.0565
  • Logps/rejected: -0.6258
  • Logps/chosen: -0.5693
  • Logits/rejected: -3.4036
  • Logits/chosen: -3.4095

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: 6e-07
  • 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
1.4828 0.8573 400 1.5201 -0.5693 -0.6258 0.5691 0.0565 -0.6258 -0.5693 -3.4036 -3.4095

Framework versions

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