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Kuongan/
CS221-distilbert-base-uncased-finetuned-semeval

Name: CS221-distilbert-base-uncased-finetuned-semeval
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distilbert/distilbert-base-uncased

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CS221-distilbert-base-uncased-finetuned-semeval

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

Loss: 0.4379
F1: 0.7152
Roc Auc: 0.7863
Accuracy: 0.4134

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: 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: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.5098	1.0	139	0.5033	0.5340	0.6705	0.2022
0.4132	2.0	278	0.4283	0.6646	0.7497	0.3773
0.3129	3.0	417	0.4051	0.7099	0.7818	0.4025
0.2507	4.0	556	0.4146	0.7072	0.7795	0.3935
0.16	5.0	695	0.4379	0.7152	0.7863	0.4134
0.1069	6.0	834	0.4643	0.7140	0.7845	0.4079
0.0873	7.0	973	0.5064	0.7060	0.7784	0.4025
0.0581	8.0	1112	0.5336	0.7119	0.7828	0.4206

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Kuongan/CS221-distilbert-base-uncased-finetuned-semeval

CS221-distilbert-base-uncased-finetuned-semeval

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Kuongan/
CS221-distilbert-base-uncased-finetuned-semeval