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LiLT-finetuned – AI Model by Saed2023 | AlphaNeural AI
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Saed2023
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LiLT-finetuned
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transformers
pytorch
tensorboard
lilt
token-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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LiLT-finetuned
This model is a fine-tuned version of
SCUT-DLVCLab/lilt-roberta-en-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.7302
Precision: 0.2787
Recall: 0.2982
F1: 0.2881
Accuracy: 0.7616
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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 500
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
No log
41.67
250
1.4739
0.2667
0.2807
0.2735
0.7632
0.1955
83.33
500
1.7302
0.2787
0.2982
0.2881
0.7616
Framework versions
Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3
