This model is a fine-tuned version of distilbert-base-uncased on the gokulsrinivasagan/processed_wikitext-103-raw-v1-ld dataset. It achieves the following results on the evaluation set:

Loss: 1.3380
Accuracy: 0.7016

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: 0.0001
train_batch_size: 176
eval_batch_size: 176
seed: 10
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
lr_scheduler_warmup_steps: 10000
num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8936	7.6923	10000	1.8034	0.6030
1.2199	15.3846	20000	1.3846	0.6875
1.0198	23.0769	30000	1.3380	0.7016

Framework versions

Transformers 4.51.0.dev0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

gokulsrinivasagan/bert_base_train_book_ent_40p_inv

bert_base_train_book_ent_40p_inv

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gokulsrinivasagan/
bert_base_train_book_ent_40p_inv