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genki10/ASAP_FineTuningBERT_UnAugV7_k1_task1_organization_k1_k1_fold0

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face

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ASAPFineTuningBERTUnAugV7k1task1organizationk1k1fold0

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

—Loss: 0.6251
—Qwk: 0.6140
—Mse: 0.6251
—Rmse: 0.7907

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: 64
—evalbatchsize: 64
—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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	1	15.8637	0.0	15.8637	3.9829
No log	2.0	2	15.2024	0.0	15.2023	3.8990
No log	3.0	3	14.3868	0.0	14.3868	3.7930
No log	4.0	4	13.0865	-0.0015	13.0865	3.6175
No log	5.0	5	11.3368	-0.0061	11.3368	3.3670
No log	6.0	6	9.4960	0.0054	9.4960	3.0816
No log	7.0	7	7.9075	0.0018	7.9075	2.8120
No log	8.0	8	7.0744	0.0	7.0744	2.6598
No log	9.0	9	6.5847	-0.0075	6.5847	2.5661
No log	10.0	10	5.5170	0.0294	5.5170	2.3488
No log	11.0	11	4.7434	0.0115	4.7434	2.1779
No log	12.0	12	4.4171	0.0115	4.4171	2.1017
No log	13.0	13	3.8355	0.0115	3.8355	1.9584
No log	14.0	14	3.3352	0.0077	3.3352	1.8263
No log	15.0	15	3.1365	0.0077	3.1365	1.7710
No log	16.0	16	2.7767	0.0039	2.7767	1.6664
No log	17.0	17	2.3713	0.1312	2.3713	1.5399
No log	18.0	18	2.0397	0.0635	2.0397	1.4282
No log	19.0	19	1.8001	0.0646	1.8001	1.3417
No log	20.0	20	1.6033	0.0583	1.6033	1.2662
No log	21.0	21	1.4407	0.0520	1.4407	1.2003
No log	22.0	22	1.3110	0.0418	1.3110	1.1450
No log	23.0	23	1.1683	0.0418	1.1683	1.0809
No log	24.0	24	1.0362	0.0418	1.0362	1.0179
No log	25.0	25	0.9642	0.0418	0.9642	0.9820
No log	26.0	26	0.9283	0.0520	0.9283	0.9635
No log	27.0	27	0.8699	0.1371	0.8699	0.9327
No log	28.0	28	0.8183	0.2990	0.8183	0.9046
No log	29.0	29	0.7864	0.3500	0.7864	0.8868
No log	30.0	30	0.7109	0.4283	0.7109	0.8432
No log	31.0	31	0.6432	0.4444	0.6432	0.8020
No log	32.0	32	0.6283	0.4023	0.6283	0.7926
No log	33.0	33	0.6407	0.4163	0.6407	0.8004
No log	34.0	34	0.6457	0.4494	0.6457	0.8036
No log	35.0	35	0.6076	0.4648	0.6076	0.7795
No log	36.0	36	0.6558	0.5077	0.6558	0.8098
No log	37.0	37	0.6410	0.5158	0.6410	0.8006
No log	38.0	38	0.5917	0.5132	0.5917	0.7692
No log	39.0	39	0.5776	0.5332	0.5776	0.7600
No log	40.0	40	0.5774	0.5672	0.5774	0.7599
No log	41.0	41	0.5790	0.5505	0.5790	0.7609
No log	42.0	42	0.5902	0.5436	0.5902	0.7682
No log	43.0	43	0.5855	0.5614	0.5855	0.7652
No log	44.0	44	0.6206	0.5653	0.6206	0.7878
No log	45.0	45	0.7227	0.5175	0.7227	0.8501
No log	46.0	46	0.7389	0.5155	0.7389	0.8596
No log	47.0	47	0.6470	0.5939	0.6470	0.8044
No log	48.0	48	0.5764	0.5994	0.5764	0.7592
No log	49.0	49	0.5905	0.5805	0.5905	0.7685
No log	50.0	50	0.6055	0.5916	0.6055	0.7781
No log	51.0	51	0.6533	0.5831	0.6533	0.8083
No log	52.0	52	0.6988	0.5824	0.6988	0.8360
No log	53.0	53	0.6683	0.6159	0.6683	0.8175
No log	54.0	54	0.6025	0.6331	0.6025	0.7762
No log	55.0	55	0.5895	0.6213	0.5895	0.7678
No log	56.0	56	0.6049	0.6105	0.6049	0.7778
No log	57.0	57	0.6211	0.6036	0.6211	0.7881
No log	58.0	58	0.6365	0.5954	0.6365	0.7978
No log	59.0	59	0.6893	0.6001	0.6893	0.8302
No log	60.0	60	0.6929	0.5944	0.6929	0.8324
No log	61.0	61	0.6891	0.5954	0.6891	0.8301
No log	62.0	62	0.6628	0.6039	0.6628	0.8141
No log	63.0	63	0.5907	0.6331	0.5907	0.7686
No log	64.0	64	0.5733	0.6159	0.5733	0.7572
No log	65.0	65	0.5811	0.6083	0.5811	0.7623
No log	66.0	66	0.5932	0.5998	0.5932	0.7702
No log	67.0	67	0.6359	0.6156	0.6359	0.7974
No log	68.0	68	0.7307	0.5787	0.7307	0.8548
No log	69.0	69	0.7660	0.5701	0.7660	0.8752
No log	70.0	70	0.7621	0.5878	0.7621	0.8730
No log	71.0	71	0.6861	0.6352	0.6861	0.8283
No log	72.0	72	0.6257	0.6535	0.6257	0.7910
No log	73.0	73	0.6137	0.6491	0.6137	0.7834
No log	74.0	74	0.6362	0.6354	0.6362	0.7976
No log	75.0	75	0.6685	0.6082	0.6685	0.8176
No log	76.0	76	0.7092	0.6054	0.7092	0.8421
No log	77.0	77	0.7434	0.6085	0.7434	0.8622
No log	78.0	78	0.7616	0.6072	0.7616	0.8727
No log	79.0	79	0.7366	0.6150	0.7366	0.8583
No log	80.0	80	0.6864	0.6347	0.6864	0.8285
No log	81.0	81	0.6409	0.6224	0.6409	0.8006
No log	82.0	82	0.6251	0.6140	0.6251	0.7907

Framework versions

—Transformers 4.47.0
—Pytorch 2.5.1+cu121
—Datasets 3.2.0
—Tokenizers 0.21.0