CONTEXT_two – AI Model by SharonTudi | AlphaNeural AI

You can deploy this model and start earning money today!

SharonTudi/
CONTEXT_two

like

0

text-classification

generated_from_trainer

distilbert/distilbert-base-cased

autotrain_compatible

endpoints_compatible

Views

No views yet

CONTEXT_two

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

Loss: 0.9806
Precision: 0.6800
Recall: 0.6711
F1: 0.6715
Accuracy: 0.6711

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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.3915	0.31	15	1.3670	0.4926	0.4211	0.3467	0.4211
1.3405	0.62	30	1.3368	0.6504	0.4737	0.4176	0.4737
1.3104	0.94	45	1.2744	0.6319	0.5526	0.5575	0.5526
1.2038	1.25	60	1.1973	0.6648	0.6053	0.6130	0.6053
1.1289	1.56	75	1.1413	0.6826	0.6842	0.6827	0.6842
1.0146	1.88	90	1.0708	0.6920	0.6316	0.6313	0.6316
0.9391	2.19	105	1.0283	0.6488	0.6184	0.6174	0.6184
0.9295	2.5	120	0.9971	0.7229	0.6974	0.7025	0.6974
0.8569	2.81	135	0.9806	0.6800	0.6711	0.6715	0.6711

Framework versions

Transformers 4.37.1
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1