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finetuning-emotion-model – AI Model by DicksonMassawe | AlphaNeural AI
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finetuning-emotion-model
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transformers
pytorch
tensorboard
distilbert
text-classification
generated_from_trainer
emotion
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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finetuning-emotion-model
This model is a fine-tuned version of
distilbert-base-uncased
on the emotion dataset. It achieves the following results on the evaluation set:
Loss: 0.1508
Accuracy: 0.936
F1: 0.9362
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: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
1.0
250
0.2633
0.9135
0.9126
0.5024
2.0
500
0.1717
0.9285
0.9289
0.5024
3.0
750
0.1560
0.9325
0.9330
0.1253
4.0
1000
0.1508
0.936
0.9362
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3
