PRESTO
Collection
PRESTO: Progressive Pretraining Enhances Synthetic Chemistry Outcomes • 4 items • Updated
OpenMol/mol-vicuna-7b-v1.5-uspto_tpl-sft
This model is a fine-tuned version of lmsys/vicuna-7b-v1.5 on the uspto_1k_tpl 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 10.0
- mixed_precision_training: Native AMP
- lora_target: all
- lora_rank: 64
Training results
Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for IDEA-AI4S/mol-vicuna-7b-v1.5-uspto_tpl-sft
Base model
lmsys/vicuna-7b-v1.5