Version_weird_ASAP_FineTuningBERT_AugV12_k6_task1_organization_k6_k6_fold2

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: 0.6802
• Qwk: 0.6349
• Mse: 0.6798
• Rmse: 0.8245

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use 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: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	2	13.0928	-0.0002	13.0932	3.6185
No log	2.0	4	8.4118	0.0018	8.4122	2.9004
No log	3.0	6	6.5166	0.0	6.5170	2.5528
No log	4.0	8	6.3293	0.0	6.3296	2.5159
No log	5.0	10	6.1797	0.0	6.1800	2.4860
No log	6.0	12	5.9975	-0.0035	5.9978	2.4490
No log	7.0	14	5.7096	0.0	5.7099	2.3895
No log	8.0	16	5.1896	0.0	5.1900	2.2782
No log	9.0	18	4.6046	0.0	4.6050	2.1459
No log	10.0	20	3.9474	0.0	3.9478	1.9869
No log	11.0	22	3.4368	0.0	3.4372	1.8540
No log	12.0	24	2.9808	0.0	2.9813	1.7266
No log	13.0	26	2.3124	0.0981	2.3129	1.5208
No log	14.0	28	1.8731	0.0910	1.8735	1.3688
No log	15.0	30	1.6405	0.0727	1.6411	1.2810
No log	16.0	32	1.1913	0.0241	1.1917	1.0917
No log	17.0	34	1.0843	0.0399	1.0847	1.0415
No log	18.0	36	0.8099	0.2838	0.8103	0.9001
No log	19.0	38	0.7423	0.3698	0.7426	0.8617
No log	20.0	40	0.6877	0.3649	0.6879	0.8294
No log	21.0	42	0.6172	0.3423	0.6172	0.7856
No log	22.0	44	0.5828	0.4426	0.5828	0.7634
No log	23.0	46	0.6130	0.3845	0.6128	0.7828
No log	24.0	48	0.6061	0.5110	0.6057	0.7783
No log	25.0	50	0.5261	0.5484	0.5259	0.7252
No log	26.0	52	0.5548	0.5754	0.5543	0.7445
No log	27.0	54	0.7476	0.5464	0.7467	0.8641
No log	28.0	56	0.5574	0.6118	0.5570	0.7463
No log	29.0	58	1.0564	0.5366	1.0552	1.0272
No log	30.0	60	0.7092	0.6182	0.7085	0.8417
No log	31.0	62	0.9478	0.5750	0.9468	0.9730
No log	32.0	64	0.6573	0.6295	0.6570	0.8105
No log	33.0	66	0.8658	0.6047	0.8652	0.9302
No log	34.0	68	0.6835	0.6287	0.6832	0.8266
No log	35.0	70	0.6141	0.6418	0.6141	0.7836
No log	36.0	72	1.0272	0.5596	1.0266	1.0132
No log	37.0	74	0.7951	0.6114	0.7946	0.8914
No log	38.0	76	0.5806	0.6252	0.5806	0.7620
No log	39.0	78	1.0022	0.5622	1.0015	1.0007
No log	40.0	80	0.9199	0.5602	0.9193	0.9588
No log	41.0	82	0.5551	0.6618	0.5550	0.7450
No log	42.0	84	0.7389	0.6142	0.7384	0.8593
No log	43.0	86	0.6501	0.6313	0.6497	0.8060
No log	44.0	88	0.7496	0.5517	0.7496	0.8658
No log	45.0	90	0.6888	0.6186	0.6883	0.8297
No log	46.0	92	0.7045	0.6212	0.7040	0.8390
No log	47.0	94	0.5998	0.6555	0.5995	0.7743
No log	48.0	96	0.9512	0.5630	0.9505	0.9749
No log	49.0	98	0.9873	0.5547	0.9866	0.9933
No log	50.0	100	0.5912	0.6430	0.5910	0.7688
No log	51.0	102	0.6384	0.5928	0.6384	0.7990
No log	52.0	104	0.6819	0.6274	0.6814	0.8255
No log	53.0	106	0.8579	0.5785	0.8572	0.9259
No log	54.0	108	0.5919	0.6542	0.5916	0.7692
No log	55.0	110	0.6051	0.6597	0.6047	0.7777
No log	56.0	112	0.8593	0.5877	0.8586	0.9266
No log	57.0	114	0.7627	0.6084	0.7621	0.8730
No log	58.0	116	0.5742	0.6477	0.5739	0.7576
No log	59.0	118	0.7390	0.6085	0.7384	0.8593
No log	60.0	120	0.7279	0.6152	0.7274	0.8529
No log	61.0	122	0.5432	0.6668	0.5430	0.7369
No log	62.0	124	0.5366	0.6612	0.5363	0.7323
No log	63.0	126	0.8442	0.5733	0.8437	0.9186
No log	64.0	128	1.0095	0.5361	1.0089	1.0044
No log	65.0	130	0.6717	0.6307	0.6712	0.8193
No log	66.0	132	0.5644	0.6653	0.5641	0.7511
No log	67.0	134	0.6496	0.6421	0.6491	0.8057
No log	68.0	136	0.7608	0.6086	0.7602	0.8719
No log	69.0	138	0.6034	0.6465	0.6030	0.7765
No log	70.0	140	0.6009	0.6497	0.6004	0.7749
No log	71.0	142	0.7460	0.6083	0.7455	0.8634
No log	72.0	144	0.6620	0.6418	0.6616	0.8134
No log	73.0	146	0.5659	0.6617	0.5655	0.7520
No log	74.0	148	0.6374	0.6420	0.6369	0.7981
No log	75.0	150	0.8140	0.5834	0.8134	0.9019
No log	76.0	152	0.7097	0.6246	0.7092	0.8422
No log	77.0	154	0.5809	0.6631	0.5806	0.7620
No log	78.0	156	0.5930	0.6558	0.5926	0.7698
No log	79.0	158	0.6914	0.6366	0.6909	0.8312
No log	80.0	160	0.6861	0.6329	0.6856	0.8280
No log	81.0	162	0.6802	0.6349	0.6798	0.8245

Framework versions

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