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DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel – AI Model by muhammadravi251001 | AlphaNeural AI
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DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
mit
endpoints_compatible
us
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DEBUGG-DatasetQAS-DEBUGdataset-with-DEBUGmodel
This model is a fine-tuned version of
indolem/indobert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.6261
Exact Match: 46.0733
F1: 54.0012
Precision: 53.9579
Recall: 55.6254
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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Exact Match
F1
Precision
Recall
1.9553
0.5
306
1.9202
36.3002
44.3381
44.0903
46.4319
1.6765
1.0
612
1.6261
46.0733
54.0012
53.9579
55.6254
Framework versions
Transformers 4.27.4
Pytorch 2.0.0+cu117
Datasets 2.2.0
Tokenizers 0.13.3
