flippa-v2

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flippa-v2

This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on a mixed dataset of filtered non-refusal data, math, and code. It achieves the following results on the evaluation set:

• Loss: 0.9289

Model description

My second test of experiments using Quantitized LoRA and Mistral-7B-Instruct, trained on A100 in one hour, will increase training times and amount of data as I gain access to more GPUs.

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: 0.0002
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 2
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Framework versions

• PEFT 0.9.0
• Transformers 4.38.1
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2