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results – AI Model by ashuc27 | AlphaNeural AI
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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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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: 0.2314
Accuracy: 0.9305
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: 2.8e-05
train_batch_size: 4
eval_batch_size: 64
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
Accuracy
0.4298
1.0
4000
0.4243
0.9085
0.2389
2.0
8000
0.3465
0.922
0.1856
3.0
12000
0.2700
0.929
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
