da_distilbert – AI Model by gc394 | AlphaNeural AI

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gc394/
da_distilbert

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distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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da_distilbert

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

Loss: 1.6301

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: 15

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	130	2.0998
No log	2.0	260	1.9483
No log	3.0	390	1.8376
2.1352	4.0	520	1.8386
2.1352	5.0	650	1.7713
2.1352	6.0	780	1.7591
2.1352	7.0	910	1.7380
1.8059	8.0	1040	1.6942
1.8059	9.0	1170	1.6574
1.8059	10.0	1300	1.6882
1.8059	11.0	1430	1.6419
1.7023	12.0	1560	1.6442
1.7023	13.0	1690	1.6709
1.7023	14.0	1820	1.6300
1.7023	15.0	1950	1.6165

Framework versions

Transformers 4.40.1
Pytorch 2.4.0.dev20240502
Datasets 2.19.0
Tokenizers 0.19.1