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OTE-ABSA-Qarib-DAPT-LABR-run1 – AI Model by salohnana2018 | AlphaNeural AI
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salohnana2018
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OTE-ABSA-Qarib-DAPT-LABR-run1
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
autotrain_compatible
endpoints_compatible
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OTE-ABSA-Qarib-DAPT-LABR-run1
This model is a fine-tuned version of
salohnana2018/Qarib-domianAdaption-OTE-ABSA-LABR
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1353
Precision: 0.7645
Recall: 0.7762
F1: 0.7703
Accuracy: 0.9509
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: 25
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.2003
1.0
121
0.1354
0.7193
0.7970
0.7562
0.9461
0.1047
2.0
242
0.1262
0.8056
0.7213
0.7611
0.9519
0.0754
3.0
363
0.1353
0.7645
0.7762
0.7703
0.9509
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
