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: 0.5408
Accuracy: 0.8503

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: 200
eval_batch_size: 200
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
1.0131	8.7413	10000	0.8705	0.7563
0.5417	17.4825	20000	0.5408	0.8503

Framework versions

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

gokulsrinivasagan/tinybert_train_book_ent_15p_inv

tinybert_train_book_ent_15p_inv

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gokulsrinivasagan/
tinybert_train_book_ent_15p_inv