MetaMathQA_Mistral-7B-v0.1-BNB-NF4_LORA_ADAPTER_96rank
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset.
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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: cosine
- num_epochs: 3.0
Training results
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.4.0+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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Model tree for oftverse/MetaMathQA_Mistral-7B-v0.1-BNB-NF4_LORA_ADAPTER_96rank
Base model
mistralai/Mistral-7B-v0.1