distilbert-base-uncased-finetuned-radiology-txt – AI Model by josejames00 | AlphaNeural AI

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josejames00/
distilbert-base-uncased-finetuned-radiology-txt

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-finetuned-radiology-txt

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3534
F1: 0.5200
Avg Roc Auc: 0.6870
Accuracy: 0.3145

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: 1e-05
train_batch_size: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Avg Roc Auc	Accuracy
0.4674	1.0	147	0.4190	0.4385	0.6434	0.2559
0.4122	2.0	294	0.3847	0.4603	0.6541	0.2923
0.3826	3.0	441	0.3659	0.4621	0.6543	0.3134
0.3657	4.0	588	0.3593	0.4987	0.6746	0.3126
0.3565	5.0	735	0.3561	0.5311	0.6950	0.3055
0.3528	6.0	882	0.3542	0.5227	0.6890	0.3113
0.3482	7.0	1029	0.3534	0.5200	0.6870	0.3145

Framework versions

Transformers 4.26.1
Pytorch 1.13.1
Datasets 2.11.0
Tokenizers 0.13.2