metadata

tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: correct_twitter_RoBERTa_token_itr0_1e-05_webDiscourse_01_03_2022-15_30_39
    results: []

correct_twitter_RoBERTa_token_itr0_1e-05_webDiscourse_01_03_2022-15_30_39

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: 0.6169
Precision: 0.0031
Recall: 0.0357
F1: 0.0057
Accuracy: 0.6464

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	10	0.6339	0.0116	0.0120	0.0118	0.6662
No log	2.0	20	0.6182	0.0064	0.0120	0.0084	0.6688
No log	3.0	30	0.6139	0.0029	0.0241	0.0052	0.6659
No log	4.0	40	0.6172	0.0020	0.0241	0.0037	0.6622
No log	5.0	50	0.6165	0.0019	0.0241	0.0036	0.6599

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3