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AlBert-finetuned-emotion – AI Model by iaminhridoy | AlphaNeural AI
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AlBert-finetuned-emotion
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transformers
tensorboard
safetensors
albert
text-classification
generated_from_trainer
emotion
albert/albert-base-v2
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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AlBert-finetuned-emotion
This model is a fine-tuned version of
albert-base-v2
on the emotion dataset. It achieves the following results on the evaluation set:
Loss: 0.2185
Accuracy: 0.9325
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: 3.069458879876956e-05
train_batch_size: 16
eval_batch_size: 16
seed: 22
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4279
1.0
1000
0.3697
0.888
0.2448
2.0
2000
0.2732
0.914
0.1731
3.0
3000
0.2270
0.923
0.1305
4.0
4000
0.2193
0.9285
0.1053
5.0
5000
0.2185
0.9325
Framework versions
Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2
