README.md

metadata

license: mit
tags:
  - generated_from_trainer
model-index:
  - name: verdict-classifier-trinary
    results: []

verdict-classifier-trinary

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

• Loss: 0.1258
• F1 Macro: 0.8408
• F1 Misinformation: 0.9751
• F1 Factual: 0.9508
• F1 Other: 0.5965
• Prec Macro: 0.8323
• Prec Misinformation: 0.9818
• Prec Factual: 1.0
• Prec Other: 0.5152

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
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 462
• num_epochs: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	F1 Misinformation	F1 Factual	F1 Other	Prec Macro	Prec Misinformation	Prec Factual	Prec Other
1.034	0.98	57	0.9960	0.3136	0.9408	0.0	0.0	0.2961	0.8882	0.0	0.0
0.968	1.98	114	0.8945	0.3136	0.9408	0.0	0.0	0.2961	0.8882	0.0	0.0
0.9253	2.98	171	0.7182	0.3136	0.9408	0.0	0.0	0.2961	0.8882	0.0	0.0
0.8215	3.98	228	0.3112	0.4795	0.9454	0.0	0.4932	0.4351	0.9381	0.0	0.3673
0.5073	4.98	285	0.1564	0.8272	0.9703	0.9355	0.5758	0.8025	0.9883	0.9667	0.4524
0.3046	5.98	342	0.1258	0.8408	0.9751	0.9508	0.5965	0.8323	0.9818	1.0	0.5152
0.1971	6.98	399	0.1540	0.8458	0.9796	0.9538	0.6038	0.8258	0.9863	0.9394	0.5517
0.1494	7.98	456	0.1779	0.8504	0.9737	0.9524	0.625	0.8195	0.9907	0.9677	0.5

Framework versions

• Transformers 4.11.3
• Pytorch 1.9.0+cu102
• Datasets 1.9.0
• Tokenizers 0.10.2