bert-dair-ai-emotion – AI Model by katsuchi | AlphaNeural AI

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katsuchi/
bert-dair-ai-emotion

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google-bert/bert-base-cased

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bert-dair-ai-emotion

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1341
F1: 0.8647

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.0127	1.0	48	0.1385	0.8670
0.0208	2.0	96	0.1379	0.8351
0.0076	3.0	144	0.1452	0.8351
0.0015	4.0	192	0.1336	0.8647
0.0133	5.0	240	0.1341	0.8647

Framework versions

PEFT 0.13.2
Transformers 4.48.0
Pytorch 2.4.1+cu124
Datasets 3.0.1
Tokenizers 0.21.0