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robertita-cased-finetuned-fact – AI Model by filevich | AlphaNeural AI
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filevich
/
robertita-cased-finetuned-fact
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transformers
pytorch
roberta
token-classification
generated_from_trainer
es
fact2020
filevich/robertita-cased
finetune
mit
model-index
autotrain_compatible
endpoints_compatible
us
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robertita-cased-finetuned-fact
This model is a fine-tuned version of
filevich/robertita-cased
on the fact2020 dataset. It achieves the following results on the evaluation set:
Loss: 0.0402
Precision: 0.9958
Recall: 0.9908
F1: 0.9915
Accuracy: 0.9908
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: 6e-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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
1.0
116
0.0372
0.9947
0.9889
0.9895
0.9889
No log
2.0
232
0.0388
0.9961
0.9903
0.9913
0.9903
No log
3.0
348
0.0402
0.9958
0.9908
0.9915
0.9908
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.14.4
Tokenizers 0.13.3
