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Mistral-Nemo-Multilingual-Constitutional-AI

This model is a fine-tuned version of mistralai/Mistral-Nemo-Base-2407 on the pbevan11/multilingual-constitutional-preference-pairs and the pbevan11/ultrafeedback_binarized_multilingual datasets. It achieves the following results on the evaluation set:

  • Loss: 1.3986

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: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 256
  • total_eval_batch_size: 64
  • 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
1.605 0.9811 13 1.3986

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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Datasets used to train pbevan11/Mistral-Nemo-Multilingual-Constitutional-AI-SFT