results – AI Model by Kirkos27 | AlphaNeural AI

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Kirkos27/
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text-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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results

This model is a fine-tuned version of google-bert/bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0462
Accuracy: 0.565

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: 4
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 15
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6966	0.12	30	1.6482	0.205
1.6111	0.24	60	1.5500	0.312
1.5634	0.36	90	1.4253	0.391
1.4389	0.48	120	1.2866	0.429
1.3507	0.6	150	1.2292	0.466
1.3072	0.72	180	1.2251	0.435
1.2346	0.84	210	1.3498	0.412
1.3884	0.96	240	1.1693	0.515
1.0748	1.08	270	1.2255	0.474
1.02	1.2	300	1.2691	0.475
1.0354	1.32	330	1.1937	0.48
1.0622	1.44	360	1.1304	0.512
1.0289	1.56	390	1.2823	0.465
1.1433	1.6800	420	1.0603	0.527
1.0125	1.8	450	1.0753	0.522
0.8716	1.92	480	1.0901	0.532
0.8761	2.04	510	1.0462	0.565
0.6857	2.16	540	1.0626	0.555
0.7674	2.2800	570	1.0799	0.545
0.6676	2.4	600	1.0843	0.546
0.6254	2.52	630	1.1148	0.551
0.6813	2.64	660	1.1227	0.553
0.7043	2.76	690	1.1267	0.558
0.4643	2.88	720	1.1227	0.551
0.6665	3.0	750	1.1222	0.557

Framework versions

Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1