DistillBERT-Political-Finetune – AI Model by harshal-11 | AlphaNeural AI

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harshal-11/
DistillBERT-Political-Finetune

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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DistillBERT-Political-Finetune

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3916
Accuracy: 0.8380
F1: 0.8287
Precision: 0.8410
Recall: 0.8195

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: 8
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.5547	1.0	3845	0.3916	0.8380	0.8287	0.8410	0.8195
0.5061	2.0	7690	0.4957	0.8523	0.8409	0.8550	0.8309
0.1709	3.0	11535	0.5732	0.8575	0.8449	0.8541	0.8376
0.0965	4.0	15380	0.6933	0.8559	0.8438	0.8478	0.8406
0.063	5.0	19225	0.8462	0.8583	0.8444	0.8456	0.8433

Framework versions

Transformers 4.40.2
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1