This model is a fine-tuned version of distilbert-base-uncased on the sem_eval2010_task8 dataset. It achieves the following results on the evaluation set:

Loss: 0.6704
Accuracy: 0.8314

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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.9556	1.0	800	0.7859	0.7814
0.6136	2.0	1600	0.6069	0.8193
0.4314	3.0	2400	0.6179	0.8211
0.2315	4.0	3200	0.6617	0.8281
0.1655	5.0	4000	0.6704	0.8314

Framework versions

Transformers 4.17.0
Pytorch 1.10.0+cu111
Datasets 1.18.4
Tokenizers 0.11.6

leonadase/distilbert-base-uncased-finetuned-sem

distilbert-base-uncased-finetuned-sem

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

leonadase/
distilbert-base-uncased-finetuned-sem