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-2e-5
    results: []

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