finetuning-sentiment-model-neologisms-distilbert-dora – AI Model by PriyadarshiniTamilselvan | AlphaNeural AI

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PriyadarshiniTamilselvan/
finetuning-sentiment-model-neologisms-distilbert-dora

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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finetuning-sentiment-model-neologisms-distilbert-dora

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: 1.1534
Accuracy: 0.5837
F1: 0.5952
Precision: 0.6232
Recall: 0.5837

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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.3385	1.0	1665	1.1534	0.5837	0.5952	0.6232	0.5837
0.3628	2.0	3330	1.1411	0.5765	0.5872	0.6234	0.5765
0.2338	3.0	4995	1.8058	0.5607	0.5736	0.6147	0.5607
0.1158	4.0	6660	2.3957	0.58	0.5883	0.6095	0.58
0.1005	5.0	8325	2.8964	0.5777	0.5860	0.6159	0.5777

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3