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: 0.2377
Accuracy: 0.91
F1: 0.9100

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: 16
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2263	1.0	2500	0.2362	0.9088	0.9088

Framework versions

Transformers 4.48.3
Pytorch 2.10.0+cu128
Datasets 3.2.0
Tokenizers 0.21.4

TrinhHoangKhang/TEST-distilbert-imdb-sentiment

TEST-distilbert-imdb-sentiment

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

TrinhHoangKhang/
TEST-distilbert-imdb-sentiment