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checkpoints – AI Model by suyingxi0 | AlphaNeural AI
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checkpoints
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transformers
safetensors
biogpt
token-classification
generated_from_trainer
ncbi_disease
microsoft/biogpt
finetune
mit
model-index
endpoints_compatible
us
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checkpoints
This model is a fine-tuned version of
microsoft/biogpt
on the ncbi_disease dataset. It achieves the following results on the evaluation set:
Loss: 0.0876
Precision: 0.7284
Recall: 0.8073
F1: 0.7658
Accuracy: 0.9778
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0425
1.0
680
0.0668
0.6871
0.7675
0.7251
0.9786
0.0399
2.0
1360
0.0656
0.7100
0.8056
0.7548
0.9803
0.0154
3.0
2040
0.0905
0.7190
0.8030
0.7587
0.9803
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 3.6.0
Tokenizers 0.22.2
