dbw-bert-large-1.1 – AI Model by Sacralet | AlphaNeural AI

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Sacralet/
dbw-bert-large-1.1

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generated_from_trainer

google-bert/bert-large-uncased

autotrain_compatible

endpoints_compatible

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dbw-bert-large-1.1

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

Loss: 0.0263

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.0616	0.09	100	0.0571
0.0516	0.18	200	0.0438
0.0417	0.27	300	0.0349
0.0372	0.36	400	0.0319
0.0317	0.44	500	0.0306
0.0309	0.53	600	0.0294
0.0287	0.62	700	0.0286
0.029	0.71	800	0.0273
0.0351	0.8	900	0.0265
0.0252	0.89	1000	0.0262
0.0226	0.98	1100	0.0263

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1