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MedAware – AI Model by keivalya | AlphaNeural AI
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keivalya
/
MedAware
like
0
pytorch
tensorboard
generated_from_trainer
text-generation
en
keivalya/MedQuad-MedicalQnADataset
apache-2.0
us
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Model card
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MedAware
This model is a fine-tuned version of
euclaise/falcon_1b_stage2
on MedQuAD: Medical Question Answering 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: 0.0002
train_batch_size: 4
eval_batch_size: 8
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: cosine
lr_scheduler_warmup_ratio: 0.05
num_epochs: 1
Training results
Training steps: 1025/1025; time- 2:45:21
Steps
Training_loss
500
1.273800
1000
1.133000
TrainOutput(global_step=1025, training_loss=1.1994486794820647, metrics={'train_runtime': 9932.0844, 'train_samples_per_second': 1.652, 'train_steps_per_second': 0.103, 'total_flos': 3.2484758758785024e+16, 'train_loss': 1.1994486794820647, 'epoch': 1.0})
Framework versions
Transformers 4.30.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
