emotion-gpt2-lora – AI Model by leonvanbokhorst | AlphaNeural AI

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emotion-gpt2-lora

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emotion-gpt2-lora

This model is a fine-tuned version of openai-community/gpt2 on the emotion dataset. It achieves the following results on the evaluation set:

Loss: 0.1521
Accuracy: 0.933
F1: 0.9334
Precision: 0.9347
Recall: 0.933

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: 0.0005
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	Precision	Recall
No log	1.0	250	0.3191	0.8895	0.8902	0.8933	0.8895
0.6939	2.0	500	0.1939	0.935	0.9349	0.9352	0.935
0.6939	3.0	750	0.1689	0.931	0.9315	0.9329	0.931
0.1897	4.0	1000	0.1521	0.933	0.9334	0.9347	0.933

Framework versions

PEFT 0.10.0
Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1