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: 0.1425
Accuracy: 0.9355
F1: 0.9356

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: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	125	0.1892	0.926	0.9266
0.2034	2.0	250	0.1571	0.9315	0.9322
0.2034	3.0	375	0.1498	0.9335	0.9338
0.1109	4.0	500	0.1425	0.9355	0.9356

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0

Abdelrahman-hassan66/distilbert-base-uncased-finetuned-emotion

distilbert-base-uncased-finetuned-emotion

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Abdelrahman-hassan66/
distilbert-base-uncased-finetuned-emotion