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	1	9.7976	0.0079	9.7965	3.1299
No log	2.0	2	8.7688	0.0	8.7670	2.9609
No log	3.0	3	8.4426	0.0	8.4409	2.9053
No log	4.0	4	8.0289	0.0	8.0272	2.8332
No log	5.0	5	7.3771	0.0	7.3755	2.7158
No log	6.0	6	6.5052	0.0003	6.5038	2.5503
No log	7.0	7	5.7228	0.0269	5.7214	2.3919
No log	8.0	8	5.1325	0.0157	5.1311	2.2652
No log	9.0	9	4.5242	0.0114	4.5230	2.1267
No log	10.0	10	4.1454	0.0	4.1443	2.0357
No log	11.0	11	3.7500	0.0	3.7489	1.9362
No log	12.0	12	3.2624	0.0	3.2614	1.8059
No log	13.0	13	2.9222	0.0	2.9212	1.7092
No log	14.0	14	2.6189	0.0216	2.6179	1.6180
No log	15.0	15	2.3954	0.0729	2.3944	1.5474
No log	16.0	16	2.0757	0.0524	2.0748	1.4404
No log	17.0	17	1.8388	0.0524	1.8380	1.3557
No log	18.0	18	1.6371	0.0463	1.6363	1.2792
No log	19.0	19	1.4909	0.0202	1.4901	1.2207
No log	20.0	20	1.3400	0.0202	1.3393	1.1573
No log	21.0	21	1.2098	0.0202	1.2091	1.0996
No log	22.0	22	1.0981	0.0202	1.0975	1.0476
No log	23.0	23	1.0514	0.0202	1.0508	1.0251
No log	24.0	24	0.9857	0.0202	0.9851	0.9925
No log	25.0	25	0.8875	0.2904	0.8870	0.9418
No log	26.0	26	0.8406	0.3282	0.8401	0.9166
No log	27.0	27	0.7997	0.3655	0.7992	0.8940
No log	28.0	28	0.7984	0.2453	0.7979	0.8933
No log	29.0	29	0.7750	0.2306	0.7746	0.8801
No log	30.0	30	0.7154	0.3155	0.7150	0.8456
No log	31.0	31	0.6934	0.3261	0.6930	0.8325
No log	32.0	32	0.7327	0.2415	0.7324	0.8558
No log	33.0	33	0.7396	0.2415	0.7394	0.8599
No log	34.0	34	0.6632	0.3170	0.6630	0.8142
No log	35.0	35	0.6197	0.3511	0.6195	0.7871
No log	36.0	36	0.6136	0.3563	0.6135	0.7832
No log	37.0	37	0.6911	0.3097	0.6911	0.8313
No log	38.0	38	0.6796	0.3315	0.6796	0.8244
No log	39.0	39	0.5734	0.4324	0.5733	0.7572
No log	40.0	40	0.5253	0.5200	0.5252	0.7247
No log	41.0	41	0.5290	0.5898	0.5290	0.7273
No log	42.0	42	0.5929	0.5549	0.5929	0.7700
No log	43.0	43	0.5913	0.5550	0.5912	0.7689
No log	44.0	44	0.5362	0.6421	0.5361	0.7322
No log	45.0	45	0.5572	0.5955	0.5571	0.7464
No log	46.0	46	0.5687	0.5955	0.5687	0.7541
No log	47.0	47	0.5731	0.6358	0.5730	0.7570
No log	48.0	48	0.6220	0.6160	0.6218	0.7886
No log	49.0	49	0.6216	0.6251	0.6214	0.7883
No log	50.0	50	0.5839	0.6368	0.5838	0.7640
No log	51.0	51	0.5972	0.6424	0.5971	0.7727
No log	52.0	52	0.6569	0.6181	0.6567	0.8104
No log	53.0	53	0.6483	0.6340	0.6481	0.8050
No log	54.0	54	0.6098	0.6404	0.6097	0.7808
No log	55.0	55	0.6151	0.6405	0.6149	0.7842
No log	56.0	56	0.6830	0.6257	0.6827	0.8262
No log	57.0	57	0.7025	0.6277	0.7022	0.8380
No log	58.0	58	0.6631	0.6385	0.6628	0.8141
No log	59.0	59	0.6354	0.6578	0.6352	0.7970
No log	60.0	60	0.6421	0.6582	0.6419	0.8012
No log	61.0	61	0.7318	0.6307	0.7314	0.8552
No log	62.0	62	0.7373	0.6254	0.7369	0.8584
No log	63.0	63	0.6665	0.6400	0.6663	0.8163
No log	64.0	64	0.6232	0.6295	0.6231	0.7893
No log	65.0	65	0.6168	0.6229	0.6166	0.7853
No log	66.0	66	0.6639	0.6389	0.6637	0.8147
No log	67.0	67	0.7074	0.6204	0.7071	0.8409
No log	68.0	68	0.6645	0.6343	0.6643	0.8151
No log	69.0	69	0.6291	0.6219	0.6290	0.7931
No log	70.0	70	0.6297	0.6232	0.6296	0.7935
No log	71.0	71	0.6305	0.6227	0.6304	0.7940
No log	72.0	72	0.6236	0.6354	0.6235	0.7896
No log	73.0	73	0.6060	0.6450	0.6058	0.7784
No log	74.0	74	0.5908	0.6520	0.5906	0.7685
No log	75.0	75	0.6064	0.6463	0.6062	0.7786
No log	76.0	76	0.6436	0.6460	0.6434	0.8021
No log	77.0	77	0.6540	0.6454	0.6538	0.8086
No log	78.0	78	0.6147	0.6608	0.6145	0.7839
No log	79.0	79	0.5962	0.6663	0.5961	0.7721
No log	80.0	80	0.6112	0.6662	0.6111	0.7817
No log	81.0	81	0.6607	0.6427	0.6605	0.8127
No log	82.0	82	0.7581	0.6245	0.7578	0.8705
No log	83.0	83	0.8015	0.6167	0.8012	0.8951
No log	84.0	84	0.7840	0.6241	0.7837	0.8853
No log	85.0	85	0.7243	0.6346	0.7240	0.8509
No log	86.0	86	0.6551	0.6575	0.6549	0.8093
No log	87.0	87	0.6132	0.6559	0.6131	0.7830
No log	88.0	88	0.6036	0.6400	0.6035	0.7769
No log	89.0	89	0.5995	0.6473	0.5994	0.7742
No log	90.0	90	0.6005	0.6705	0.6004	0.7749
No log	91.0	91	0.6140	0.6777	0.6138	0.7835
No log	92.0	92	0.6459	0.6500	0.6457	0.8035
No log	93.0	93	0.6987	0.6453	0.6985	0.8358
No log	94.0	94	0.7447	0.6293	0.7445	0.8628
No log	95.0	95	0.7702	0.6197	0.7699	0.8775
No log	96.0	96	0.7751	0.6212	0.7748	0.8802
No log	97.0	97	0.7656	0.6223	0.7653	0.8748
No log	98.0	98	0.7520	0.6260	0.7517	0.8670
No log	99.0	99	0.7384	0.6254	0.7381	0.8591
No log	100.0	100	0.7297	0.6296	0.7294	0.8540

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

genki10/Version3ASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

Version3ASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

genki10/
Version3ASAP_FineTuningBERT_AugV12_k3_task1_organization_k3_k3_fold3