README.md

metadata

license: mit
base_model: digitalepidemiologylab/covid-twitter-bert-v2
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: covid-twitter-bert-v2_1_4_2e-05_0.01
    results: []

covid-twitter-bert-v2_1_4_2e-05_0.01

This model is a fine-tuned version of digitalepidemiologylab/covid-twitter-bert-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1675
• Accuracy: 0.9659
• F1: 0.9117
• Precision: 0.8761
• Recall: 0.9502

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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.2014	1.0	1629	0.1675	0.9659	0.9117	0.8761	0.9502

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.3
• Tokenizers 0.13.3