medical_resoning – AI Model by carrotboardgame | AlphaNeural AI

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carrotboardgame/
medical_resoning

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text2text-generation

generated_from_trainer

google/flan-t5-base

text-generation-inference

endpoints_compatible

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medical_resoning

This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:

Loss: nan

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
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: linear
num_epochs: 3.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.0	1.0	2217	nan
0.0	2.0	4434	nan
0.0	3.0	6651	nan

Framework versions

Transformers 4.53.2
Pytorch 2.7.0+cu118
Datasets 4.0.0
Tokenizers 0.21.1