metadata

library_name: transformers
license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - liar
metrics:
  - accuracy
model-index:
  - name: liar_binaryclassifier_roberta_base
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: liar
          type: liar
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5770065075921909

liar_binaryclassifier_roberta_base

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

Loss: 0.6621
Model Preparation Time: 0.0069
Accuracy: 0.5770

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: 3e-06
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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Accuracy
0.6934	1.0	461	0.6843	0.0069	0.5553
0.6859	2.0	922	0.6815	0.0069	0.5531
0.6774	3.0	1383	0.6666	0.0069	0.5597
0.6671	4.0	1844	0.6742	0.0069	0.5748
0.6596	5.0	2305	0.6621	0.0069	0.5770

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1