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Mou11209203/
distilbert-base-uncased_classification_finetuned_news_all_adptive

Name: distilbert-base-uncased_classification_finetuned_news_all_adptive
Availability: InStock

generated_from_trainer

distilbert/distilbert-base-uncased

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distilbert-base-uncased_classification_finetuned_news_all_adptive

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

Loss: 0.3349
F1: 0.8321

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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.3684	1.0	2384	0.3509	0.7971
0.351	2.0	4768	0.3268	0.8103
0.3087	3.0	7152	0.3544	0.8244
0.2486	4.0	9536	0.3349	0.8321
0.2256	5.0	11920	0.3863	0.8315
0.2289	6.0	14304	0.3883	0.8320

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Mou11209203/distilbert-base-uncased_classification_finetuned_news_all_adptive

distilbert-base-uncased_classification_finetuned_news_all_adptive

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Mou11209203/
distilbert-base-uncased_classification_finetuned_news_all_adptive