mlfoundations-dev_-_hp_ablations_mistral_scheduler_constant_dcftv1.2-gguf

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hp_ablations_mistral_scheduler_constant_dcftv1.2 - GGUF

• Model creator: https://huggingface.co/mlfoundations-dev/
• Original model: https://huggingface.co/mlfoundations-dev/hp_ablations_mistral_scheduler_constant_dcftv1.2/

Original model description:

library_name: transformers license: apache-2.0 base_model: mistralai/Mistral-7B-v0.1 tags:

• llama-factory
• full
• generated_from_trainer model-index:
• name: hp_ablations_mistral_scheduler_constant_dcftv1.2 results: []

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hp_ablations_mistral_scheduler_constant_dcftv1.2

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the mlfoundations-dev/oh-dcft-v1.2_no-curation_gpt-4o-mini dataset. It achieves the following results on the evaluation set:

• Loss: 0.0766

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: 5e-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 8
• total_train_batch_size: 512
• total_eval_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant
• lr_scheduler_warmup_ratio: 0.1
• lr_scheduler_warmup_steps: 1738
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.46.1
• Pytorch 2.3.0
• Datasets 3.0.2
• Tokenizers 0.20.3