README.md

metadata

license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - sem_eval_2018_task_1
metrics:
  - f1
  - accuracy
model-index:
  - name: bert-finetuned-sem_eval-english
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: sem_eval_2018_task_1
          type: sem_eval_2018_task_1
          config: subtask5.english
          split: validation
          args: subtask5.english
        metrics:
          - name: F1
            type: f1
            value: 0.6611215454789374
          - name: Accuracy
            type: accuracy
            value: 0.24717832957110608

bert-finetuned-sem_eval-english

This model is a fine-tuned version of bert-base-uncased on the sem_eval_2018_task_1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3263
• F1: 0.6611
• Roc Auc: 0.7630
• Accuracy: 0.2472

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: 8
• eval_batch_size: 8
• 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	F1	Roc Auc	Accuracy
0.404	1.0	855	0.3263	0.6611	0.7630	0.2472

Framework versions

• Transformers 4.34.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1