fine-tunning-roberta-bne-hate-offensive – AI Model by esmarquez17 | AlphaNeural AI

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esmarquez17/
fine-tunning-roberta-bne-hate-offensive

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text-classification

generated_from_trainer

BSC-LT/roberta-base-bne

autotrain_compatible

endpoints_compatible

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fine-tunning-roberta-bne-hate-offensive

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

Loss: 0.6211
Hate/offensive F1: 0.8958
Hate/offensive Precision: 0.9421
Hate/offensive Recall: 0.8539
Normal F1: 0.9519
Normal Precision: 0.9308
Normal Recall: 0.9740
Micro F1: 0.9342
Acc: 0.9342
Macro F1: 0.9239
Macro Precision: 0.9364
Macro Recall: 0.9139

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: 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	Hate/offensive F1	Hate/offensive Precision	Hate/offensive Recall	Normal F1	Normal Precision	Normal Recall	Micro F1	Acc	Macro F1	Macro Precision	Macro Recall
0.2865	1.0	1064	0.3398	0.8953	0.9324	0.8610	0.9510	0.9336	0.9691	0.9332	0.9332	0.9231	0.9330	0.9150
0.1527	2.0	2128	0.3417	0.8942	0.9204	0.8695	0.9497	0.9370	0.9627	0.9318	0.9318	0.9220	0.9287	0.9161
0.047	3.0	3192	0.5626	0.8914	0.9668	0.8270	0.9518	0.9199	0.9859	0.9332	0.9332	0.9216	0.9434	0.9064
0.0145	4.0	4256	0.5874	0.8986	0.9396	0.8610	0.9528	0.9338	0.9726	0.9356	0.9356	0.9257	0.9367	0.9168
0.0029	5.0	5320	0.6211	0.8958	0.9421	0.8539	0.9519	0.9308	0.9740	0.9342	0.9342	0.9239	0.9364	0.9139

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0