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jackmedda/google-bigbird-roberta-base_finetuned_augmented_augmented_deepseek

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face

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Model Card

jackmedda/google-bigbird-roberta-basefinetunedaugmentedaugmenteddeepseek

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

—Loss: 1.3040
—Accuracy: 0.7647
—F1: 0.8571
—Precision: 0.8
—Recall: 0.9231

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
—trainbatchsize: 4
—evalbatchsize: 4
—seed: 42
—optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: linear
—num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.4568	1.0	46	0.7344	0.7	0.8235	0.7	1.0
0.6053	2.0	92	0.6889	0.7	0.8235	0.7	1.0
0.5004	3.0	138	0.6289	0.7	0.8235	0.7	1.0
0.6076	4.0	184	0.6493	0.7	0.8235	0.7	1.0
0.3798	5.0	230	0.7945	0.7	0.8235	0.7	1.0
0.2401	6.0	276	1.2776	0.7	0.8235	0.7	1.0
0.4076	7.0	322	1.1325	0.7	0.8235	0.7	1.0
0.1193	8.0	368	1.1424	0.7	0.8235	0.7	1.0
0.3332	9.0	414	0.9214	0.8	0.875	0.7778	1.0
0.1445	10.0	460	0.2424	0.9	0.9333	0.875	1.0
0.0029	11.0	506	1.6181	0.7	0.8235	0.7	1.0
0.1174	12.0	552	0.0031	1.0	1.0	1.0	1.0
0.0014	13.0	598	1.2314	0.8	0.875	0.7778	1.0
0.0011	14.0	644	1.1105	0.8	0.875	0.7778	1.0
0.0008	15.0	690	1.2286	0.8	0.875	0.7778	1.0
0.0008	16.0	736	1.2704	0.8	0.875	0.7778	1.0
0.0006	17.0	782	1.3157	0.8	0.875	0.7778	1.0
0.0005	18.0	828	1.3290	0.8	0.875	0.7778	1.0
0.0005	19.0	874	1.3752	0.8	0.875	0.7778	1.0
0.0004	20.0	920	1.3951	0.8	0.875	0.7778	1.0

Framework versions

—Transformers 4.48.3
—Pytorch 2.3.0+cu121
—Datasets 3.2.0
—Tokenizers 0.21.0