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kdrt_content_identification – AI Model by brescia | AlphaNeural AI
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brescia
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kdrt_content_identification
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
indolem/indobertweet-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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kdrt_content_identification
This model is a fine-tuned version of
indolem/indobertweet-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4682
Accuracy: 0.855
Precision: 0.855
Recall: 0.855
F1: 0.855
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
No log
1.0
101
0.6326
0.805
0.805
0.805
0.805
No log
2.0
202
0.4682
0.855
0.855
0.855
0.855
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
