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: 0.0009

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: 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
0.0246	0.2907	500	0.0049
0.0041	0.5814	1000	0.0018
0.0019	0.8721	1500	0.0012
0.001	1.1628	2000	0.0010
0.0008	1.4535	2500	0.0010
0.0003	1.7442	3000	0.0008
0.0005	2.0349	3500	0.0010
0.0003	2.3256	4000	0.0009
0.0004	2.6163	4500	0.0010
0.0002	2.9070	5000	0.0009

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

edithram23/distilbert-base-uncased

distilbert-base-uncased

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

edithram23/
distilbert-base-uncased