mistral-7b_test2
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset.
Model description
mistral-7b quantized with QLoRA and fine-tuned with 10000 randomly selected samples from MMLU axiliary training (with correct prompt format)
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2.5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- training_steps: 1000
MMLU accuracy
Overall: 61.0%
STEM: 52.33%
Humanities: 66.69%
Social Sciences: 71.33%
Other (business, health, misc.): 64.46%
Framework versions
- PEFT 0.9.1.dev0
- Transformers 4.38.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for kexinz/mistral-7b_test2
Base model
mistralai/Mistral-7B-v0.1