bert-base-uncased-issues-128-issues-128 – AI Model by tanqing2001 | AlphaNeural AI

You can deploy this model and start earning money today!

tanqing2001/
bert-base-uncased-issues-128-issues-128

like

0

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

Views

No views yet

bert-base-uncased-issues-128-issues-128

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

Loss: 1.1652

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: 32
eval_batch_size: 8
seed: 42
distributed_type: tpu
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss
2.1106	1.0	291	1.6945
1.6342	2.0	582	1.3698
1.4812	3.0	873	1.4282
1.3939	4.0	1164	1.4237
1.3419	5.0	1455	1.2666
1.2871	6.0	1746	1.3084
1.2294	7.0	2037	1.2115
1.2124	8.0	2328	1.2611
1.1791	9.0	2619	1.2653
1.1488	10.0	2910	1.2165
1.1268	11.0	3201	1.2643
1.0993	12.0	3492	1.1550
1.0963	13.0	3783	1.1520
1.0793	14.0	4074	1.0736
1.0659	15.0	4365	1.2466
1.0674	16.0	4656	1.1652

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.0