bert-large-cased-finetuned-mrpc – AI Model by gchhablani | AlphaNeural AI

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gchhablani/
bert-large-cased-finetuned-mrpc

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-large-cased-finetuned-mrpc

This model is a fine-tuned version of bert-large-cased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

Loss: 0.6274
Accuracy: 0.6838
F1: 0.8122
Combined Score: 0.7480

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: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.6441	1.0	917	0.6370	0.6838	0.8122	0.7480
0.6451	2.0	1834	0.6553	0.6838	0.8122	0.7480
0.6428	3.0	2751	0.6332	0.6838	0.8122	0.7480
0.6476	4.0	3668	0.6248	0.6838	0.8122	0.7480
0.6499	5.0	4585	0.6274	0.6838	0.8122	0.7480

Framework versions

Transformers 4.11.0.dev0
Pytorch 1.9.0
Datasets 1.12.1
Tokenizers 0.10.3