bert-because-trainer-oversample – AI Model by alenatz | AlphaNeural AI

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alenatz/
bert-because-trainer-oversample

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text-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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bert-because-trainer-oversample

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: 0.3274
Accuracy: 0.8972
F1: 0.8299
Recall: 0.8342
Precision: 0.8256

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Recall	Precision
0.6383	0.07	25	0.5128	0.7461	0.2882	0.1710	0.9167
0.5933	0.15	50	0.5335	0.7352	0.6545	0.8342	0.5385
0.4774	0.22	75	0.4369	0.8131	0.5804	0.4301	0.8925
0.4801	0.3	100	0.3538	0.8458	0.7429	0.7409	0.7448
0.3765	0.37	125	0.3890	0.8536	0.7267	0.6477	0.8278
0.3411	0.45	150	0.4052	0.8474	0.7710	0.8549	0.7021
0.2802	0.52	175	0.3509	0.8660	0.7701	0.7461	0.7956
0.2558	0.59	200	0.4704	0.8629	0.7179	0.5803	0.9412
0.4603	0.67	225	0.3298	0.8801	0.7968	0.7824	0.8118
0.3211	0.74	250	0.3053	0.8925	0.8189	0.8083	0.8298
0.2475	0.82	275	0.3052	0.8879	0.8209	0.8549	0.7895
0.2644	0.89	300	0.3688	0.8910	0.8077	0.7617	0.8596
0.3206	0.96	325	0.3332	0.8988	0.8320	0.8342	0.8299

Framework versions

Transformers 4.37.2
Pytorch 2.3.1
Datasets 2.19.1
Tokenizers 0.15.1