my_awesome_model – AI Model by dshin | AlphaNeural AI

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dshin/
my_awesome_model

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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my_awesome_model

This model is a fine-tuned version of bert-base-uncased on the mic dataset. It achieves the following results on the evaluation set:

Loss: 1.0634
Accuracy: 0.6855
F1: 0.6010
Precision: 0.6053
Recall: 0.5974

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7221	1.0	5689	0.7082	0.6943	0.5470	0.6322	0.5336
0.6334	2.0	11378	0.7100	0.7048	0.5810	0.6452	0.5573
0.5185	3.0	17067	0.7709	0.6968	0.6057	0.6162	0.6001
0.3962	4.0	22756	0.8961	0.6881	0.6050	0.6091	0.6014
0.2962	5.0	28445	1.0634	0.6855	0.6010	0.6053	0.5974

Framework versions

Transformers 4.26.1
Pytorch 1.13.1
Datasets 2.10.0
Tokenizers 0.12.1