metadata

tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: >-
      DistilBERTFINAL_ctxSentence_TRAIN_editorials_TEST_NULL_second_train_set_null_False
    results: []

DistilBERTFINAL_ctxSentence_TRAIN_editorials_TEST_NULL_second_train_set_null_False

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 4.4527
Precision: 0.2844
Recall: 0.9676
F1: 0.4395
Accuracy: 0.2991

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
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	Precision	Recall	F1	Accuracy
No log	1.0	166	0.1044	0.9742	1.0	0.9869	0.9742
No log	2.0	332	0.1269	0.9742	1.0	0.9869	0.9742
No log	3.0	498	0.1028	0.9742	1.0	0.9869	0.9742
0.0947	4.0	664	0.0836	0.9826	0.9971	0.9898	0.9799
0.0947	5.0	830	0.0884	0.9854	0.9912	0.9883	0.9771

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3