bert-base-cased-finetuned-wls-manual-9ep – AI Model by btamm12 | AlphaNeural AI

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btamm12/
bert-base-cased-finetuned-wls-manual-9ep

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google-bert/bert-base-cased

autotrain_compatible

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bert-base-cased-finetuned-wls-manual-9ep

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

Loss: 1.1883

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 9

Training results

Training Loss	Epoch	Step	Validation Loss
2.1588	0.93	7	1.8380
1.6343	2.0	15	1.6555
1.6181	2.93	22	1.5436
1.4245	4.0	30	1.4227
1.3525	4.93	37	1.4219
1.2804	6.0	45	1.3093
1.2167	6.93	52	1.2617
1.1662	8.0	60	1.2366
1.1817	8.4	63	1.2008

Framework versions

Transformers 4.31.0
Pytorch 1.11.0+cu113
Datasets 2.14.4
Tokenizers 0.13.3