bertBasev2 – AI Model by brad1141 | AlphaNeural AI

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brad1141/
bertBasev2

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bertBasev2

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

Loss: 0.0328
Precision: 0.9539
Recall: 0.9707
F1: 0.9622
Accuracy: 0.9911

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
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	Precision	Recall	F1	Accuracy
1.2004	1.0	1012	0.9504	0.2620	0.3519	0.3004	0.6856
1.0265	2.0	2024	0.6205	0.4356	0.5161	0.4725	0.7956
0.6895	3.0	3036	0.3269	0.6694	0.7302	0.6985	0.9044
0.44	4.0	4048	0.1325	0.8356	0.9091	0.8708	0.9667
0.2585	5.0	5060	0.0717	0.9259	0.9531	0.9393	0.9844
0.1722	6.0	6072	0.0382	0.9480	0.9619	0.9549	0.99
0.0919	7.0	7084	0.0328	0.9539	0.9707	0.9622	0.9911

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.1.0
Tokenizers 0.12.1