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finetuning-emotion-model – AI Model by dat-vootree | AlphaNeural AI
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finetuning-emotion-model
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onnx
safetensors
distilbert
generated_from_trainer
emotion
distilbert/distilbert-base-uncased
quantized
apache-2.0
model-index
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: 0.2169
Accuracy: 0.928
F1: 0.9279
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
No log
1.0
250
0.3225
0.902
0.9012
0.5453
2.0
500
0.2169
0.928
0.9279
Framework versions
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
