early_fusion_sentiment_False_hate_speech_False_extra_layer_True

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

• Loss: 0.5777
• Accuracy Offensive: 0.7863
• F1 Offensive: 0.7723
• Accuracy Targeted: 0.7787
• F1 Targeted: 0.7572
• Accuracy Stance: 0.7428
• F1 Stance: 0.7013

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: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Offensive	F1 Offensive	Accuracy Targeted	F1 Targeted	Accuracy Stance	F1 Stance
0.7729	1.0	1324	0.7661	0.6545	0.5178	0.6545	0.5178	0.7009	0.5777
0.7485	2.0	2648	0.7450	0.6545	0.5178	0.6545	0.5178	0.7009	0.5777
0.7392	3.0	3972	0.7296	0.6552	0.5202	0.6545	0.5178	0.7009	0.5777
0.7234	4.0	5296	0.7074	0.6809	0.5866	0.6696	0.5596	0.7009	0.5777
0.7096	5.0	6620	0.6893	0.7051	0.6508	0.6949	0.6413	0.7009	0.5777
0.6984	6.0	7944	0.6785	0.7024	0.6349	0.6990	0.6405	0.7035	0.5847
0.6829	7.0	9268	0.6607	0.7130	0.6653	0.7168	0.6843	0.7156	0.6386
0.6721	8.0	10592	0.6508	0.7187	0.6681	0.7232	0.6870	0.7179	0.6476
0.6603	9.0	11916	0.6441	0.7228	0.6728	0.7307	0.6939	0.7209	0.6528
0.6481	10.0	13240	0.6331	0.7560	0.7341	0.7383	0.7193	0.7205	0.6766
0.641	11.0	14564	0.6242	0.7496	0.7193	0.7496	0.7244	0.7296	0.6768
0.6422	12.0	15888	0.6149	0.7523	0.7225	0.7489	0.7232	0.7281	0.6776
0.6197	13.0	17212	0.6071	0.7745	0.7597	0.7579	0.7405	0.7292	0.6911
0.6175	14.0	18536	0.5984	0.7742	0.7550	0.7610	0.7411	0.7383	0.6950
0.6209	15.0	19860	0.5916	0.7904	0.7807	0.7613	0.7441	0.7372	0.7015
0.5842	16.0	21184	0.5952	0.7591	0.7322	0.7655	0.7391	0.7379	0.6918
0.6166	17.0	22508	0.5812	0.7840	0.7690	0.7749	0.7544	0.7436	0.7011
0.5952	18.0	23832	0.5829	0.7662	0.7390	0.7761	0.7477	0.7428	0.6876
0.5956	19.0	25156	0.5852	0.7659	0.7379	0.7711	0.7427	0.7485	0.6937

Framework versions

• Transformers 4.50.2
• Pytorch 2.6.0+cu124
• Datasets 3.0.1
• Tokenizers 0.21.1