Tensoic - Mistral-7B-v0.1-alpaca-2k-test
Our first fine tune of the Mistral 7B on the Alpaca-2k-test dataset. Feel free to play around!
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for Tensoic/Mistral-7B-v0.1-alpaca-2k-test
Base model
mistralai/Mistral-7B-v0.1