Version_weird_ASAP_FineTuningBERT_AugV12_k2_task1_organization_k2_k2_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: 0.9269
• Qwk: 0.5687
• Mse: 0.9258
• Rmse: 0.9622

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	1	9.5826	0.0	9.5827	3.0956
No log	2.0	2	8.1019	0.0	8.1021	2.8464
No log	3.0	3	7.0890	0.0	7.0893	2.6626
No log	4.0	4	6.5413	0.0002	6.5416	2.5576
No log	5.0	5	5.6654	0.0374	5.6657	2.3803
No log	6.0	6	4.7095	0.0137	4.7098	2.1702
No log	7.0	7	4.1714	0.0039	4.1718	2.0425
No log	8.0	8	3.9079	0.0039	3.9084	1.9770
No log	9.0	9	3.4884	0.0	3.4889	1.8679
No log	10.0	10	2.9517	0.0	2.9521	1.7182
No log	11.0	11	2.4790	0.0695	2.4794	1.5746
No log	12.0	12	2.2214	0.1275	2.2219	1.4906
No log	13.0	13	2.0889	0.0780	2.0894	1.4455
No log	14.0	14	1.8506	0.0640	1.8511	1.3606
No log	15.0	15	1.5892	0.0345	1.5897	1.2608
No log	16.0	16	1.3664	0.0280	1.3669	1.1691
No log	17.0	17	1.2312	0.0107	1.2317	1.1098
No log	18.0	18	1.1326	0.0	1.1331	1.0645
No log	19.0	19	1.0391	0.0	1.0396	1.0196
No log	20.0	20	0.9524	0.0	0.9528	0.9761
No log	21.0	21	0.8858	0.0761	0.8862	0.9414
No log	22.0	22	0.8317	0.3785	0.8321	0.9122
No log	23.0	23	0.7889	0.2637	0.7893	0.8884
No log	24.0	24	0.7606	0.2243	0.7609	0.8723
No log	25.0	25	0.7347	0.2007	0.7350	0.8573
No log	26.0	26	0.7001	0.2579	0.7003	0.8368
No log	27.0	27	0.6637	0.2584	0.6638	0.8148
No log	28.0	28	0.6365	0.2852	0.6365	0.7978
No log	29.0	29	0.6118	0.3168	0.6118	0.7822
No log	30.0	30	0.5750	0.3775	0.5749	0.7582
No log	31.0	31	0.5576	0.4241	0.5574	0.7466
No log	32.0	32	0.5521	0.4237	0.5519	0.7429
No log	33.0	33	0.5575	0.4180	0.5571	0.7464
No log	34.0	34	0.5689	0.4515	0.5685	0.7540
No log	35.0	35	0.5867	0.5406	0.5863	0.7657
No log	36.0	36	0.6104	0.5939	0.6099	0.7809
No log	37.0	37	0.6447	0.5860	0.6441	0.8025
No log	38.0	38	0.6842	0.5894	0.6836	0.8268
No log	39.0	39	0.7334	0.5654	0.7327	0.8560
No log	40.0	40	0.7524	0.5550	0.7516	0.8669
No log	41.0	41	0.7649	0.5636	0.7641	0.8741
No log	42.0	42	0.7631	0.5626	0.7622	0.8730
No log	43.0	43	0.7599	0.5761	0.7590	0.8712
No log	44.0	44	0.7768	0.5606	0.7759	0.8808
No log	45.0	45	0.7729	0.5668	0.7719	0.8786
No log	46.0	46	0.7328	0.5666	0.7319	0.8555
No log	47.0	47	0.6977	0.5691	0.6968	0.8348
No log	48.0	48	0.6681	0.5726	0.6672	0.8168
No log	49.0	49	0.6563	0.5754	0.6555	0.8096
No log	50.0	50	0.6409	0.5806	0.6402	0.8001
No log	51.0	51	0.6811	0.5757	0.6802	0.8247
No log	52.0	52	0.7586	0.5693	0.7576	0.8704
No log	53.0	53	0.7173	0.5759	0.7164	0.8464
No log	54.0	54	0.7448	0.5870	0.7438	0.8624
No log	55.0	55	0.7868	0.5802	0.7857	0.8864
No log	56.0	56	0.7218	0.6065	0.7209	0.8490
No log	57.0	57	0.7231	0.5971	0.7221	0.8498
No log	58.0	58	0.7585	0.5925	0.7574	0.8703
No log	59.0	59	0.7140	0.6104	0.7130	0.8444
No log	60.0	60	0.7255	0.6000	0.7246	0.8512
No log	61.0	61	0.7136	0.6129	0.7127	0.8442
No log	62.0	62	0.7611	0.5876	0.7601	0.8718
No log	63.0	63	0.8556	0.5550	0.8545	0.9244
No log	64.0	64	0.8184	0.5765	0.8174	0.9041
No log	65.0	65	0.7805	0.5814	0.7795	0.8829
No log	66.0	66	0.7871	0.5810	0.7861	0.8866
No log	67.0	67	0.8941	0.5683	0.8930	0.9450
No log	68.0	68	0.9501	0.5569	0.9489	0.9741
No log	69.0	69	0.8779	0.5731	0.8768	0.9364
No log	70.0	70	0.8018	0.5944	0.8009	0.8949
No log	71.0	71	0.7825	0.5809	0.7816	0.8841
No log	72.0	72	0.8254	0.5841	0.8244	0.9080
No log	73.0	73	0.9340	0.5627	0.9328	0.9658
No log	74.0	74	0.9423	0.5650	0.9410	0.9701
No log	75.0	75	0.8716	0.5855	0.8705	0.9330
No log	76.0	76	0.8740	0.5832	0.8729	0.9343
No log	77.0	77	0.8652	0.5836	0.8641	0.9296
No log	78.0	78	0.8379	0.5841	0.8369	0.9148
No log	79.0	79	0.8459	0.5799	0.8449	0.9192
No log	80.0	80	0.8681	0.5825	0.8670	0.9311
No log	81.0	81	0.9269	0.5687	0.9258	0.9622

Framework versions

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