testing – AI Model by AlexC98 | AlphaNeural AI

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testing

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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testing

This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5427
Accuracy: 0.7455

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	47	0.6397	0.6364
No log	2.0	94	0.6157	0.6788
No log	3.0	141	0.5956	0.6788
No log	4.0	188	0.5866	0.6848
No log	5.0	235	0.5727	0.6788
No log	6.0	282	0.5663	0.6970
No log	7.0	329	0.5610	0.7091
No log	8.0	376	0.5548	0.7091
No log	9.0	423	0.5536	0.7212
No log	10.0	470	0.5486	0.7273
0.583	11.0	517	0.5451	0.7273
0.583	12.0	564	0.5468	0.7333
0.583	13.0	611	0.5423	0.7394
0.583	14.0	658	0.5396	0.7394
0.583	15.0	705	0.5466	0.7394
0.583	16.0	752	0.5411	0.7455
0.583	17.0	799	0.5427	0.7455

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3