early_fusion_sentiment_True_hate_speech_True_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: 0.6361
• Accuracy Offensive: 0.7458
• F1 Offensive: 0.7275
• Accuracy Targeted: 0.7311
• F1 Targeted: 0.7067
• Accuracy Stance: 0.7232
• F1 Stance: 0.6711

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
0.7872	1.0	1324	0.7659	0.6545	0.5178	0.6545	0.5178	0.7009	0.5777
0.7576	2.0	2648	0.7524	0.6545	0.5178	0.6545	0.5178	0.7009	0.5777
0.7515	3.0	3972	0.7368	0.6548	0.5186	0.6545	0.5178	0.7009	0.5777
0.7358	4.0	5296	0.7200	0.6684	0.5556	0.6545	0.5178	0.7009	0.5777
0.7182	5.0	6620	0.7027	0.6949	0.6379	0.6862	0.6297	0.7009	0.5777
0.7087	6.0	7944	0.6987	0.6934	0.6146	0.6869	0.6161	0.7009	0.5777
0.7043	7.0	9268	0.6827	0.7100	0.6623	0.6983	0.6579	0.7013	0.5787
0.6937	8.0	10592	0.6790	0.7054	0.6452	0.6979	0.6479	0.7051	0.5979
0.6806	9.0	11916	0.6864	0.6979	0.6211	0.6971	0.6345	0.7062	0.6007
0.6762	10.0	13240	0.6626	0.7266	0.6911	0.7153	0.6902	0.7122	0.6474
0.668	11.0	14564	0.6576	0.7243	0.6887	0.7183	0.6885	0.7149	0.6397
0.6688	12.0	15888	0.6569	0.7266	0.6873	0.7209	0.6856	0.7160	0.6439
0.6576	13.0	17212	0.6512	0.7458	0.7317	0.7149	0.6988	0.7092	0.6612
0.6516	14.0	18536	0.6453	0.7443	0.7262	0.7247	0.7024	0.7145	0.6631
0.655	15.0	19860	0.6410	0.7477	0.7315	0.7277	0.7066	0.7179	0.6678
0.6368	16.0	21184	0.6429	0.7390	0.7102	0.7277	0.6975	0.7236	0.6620
0.6639	17.0	22508	0.6361	0.7458	0.7275	0.7311	0.7067	0.7232	0.6711
0.6319	18.0	23832	0.6392	0.7406	0.7115	0.7266	0.6945	0.7228	0.6556
0.6341	19.0	25156	0.6364	0.7402	0.7157	0.7300	0.7008	0.7285	0.6675

Framework versions

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