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task2_xlnet-large-cased_3_4_2e-05_0.01 – AI Model by YanJiangJerry | AlphaNeural AI
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task2_xlnet-large-cased_3_4_2e-05_0.01
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transformers
pytorch
xlnet
text-classification
generated_from_trainer
xlnet/xlnet-large-cased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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task2_xlnet-large-cased_3_4_2e-05_0.01
This model is a fine-tuned version of
xlnet-large-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9482
F1: 0.7790
Recall: 0.7790
Precision: 0.7790
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: 2e-05
train_batch_size: 4
eval_batch_size: 4
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
F1
Recall
Precision
0.8074
1.0
745
0.7084
0.7574
0.7574
0.7574
0.7665
2.0
1490
0.7881
0.7628
0.7628
0.7628
0.6739
3.0
2235
0.9482
0.7790
0.7790
0.7790
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.3
Tokenizers 0.13.3