cc_narratives_robertamodel3

This model is a fine-tuned version of nnisbett/cc-narratives_robertamodel2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.1325
• F1: 0.8278

Model description

This model classifies climate-related sentences into either normative, delay, or economic based on the argument they express.

Intended uses & limitations

More information needed

Training and evaluation data

This model was trained on transcripts of interviews with UK members of parliament.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.1795	1.0	22	0.5493	0.8459
0.1221	2.0	44	0.8102	0.8392
0.0821	3.0	66	0.6461	0.8682
0.0581	4.0	88	0.5884	0.8610
0.0352	5.0	110	0.6353	0.8878
0.0332	6.0	132	0.5653	0.9135
0.0176	7.0	154	0.5591	0.9051
0.0251	8.0	176	0.6146	0.8878
0.0152	9.0	198	0.5605	0.8963
0.0059	10.0	220	0.5578	0.8963

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3