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albert-base-v2-finetuned-emotion – AI Model by bandi2716 | AlphaNeural AI
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bandi2716
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albert-base-v2-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-base-v2-finetuned-emotion
This model is a fine-tuned version of
albert/albert-base-v2
on the emotion dataset. It achieves the following results on the evaluation set:
Loss: 0.2451
Accuracy: 0.912
F1: 0.9118
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: 64
eval_batch_size: 64
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
F1
0.9011
1.0
250
0.4077
0.877
0.8776
0.2633
2.0
500
0.2451
0.912
0.9118
Framework versions
Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
