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vi-fin-news – AI Model by tandevstag | AlphaNeural AI
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vi-fin-news
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transformers
pytorch
bert
text-classification
generated_from_trainer
FPTAI/vibert-base-cased
finetune
autotrain_compatible
endpoints_compatible
us
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vi-fin-news
This model is a fine-tuned version of
FPTAI/vibert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4509
Accuracy: 0.9136
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: 16
eval_batch_size: 16
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
0.1176
1.0
1150
0.3566
0.9181
0.0582
2.0
2300
0.4509
0.9136
Framework versions
Transformers 4.32.1
Pytorch 2.1.2
Datasets 2.12.0
Tokenizers 0.13.3
