Version_weird_ASAP_FineTuningBERT_AugV12_k1_task1_organization_k1_k1_fold4

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: 0.6719
• Qwk: 0.6355
• Mse: 0.6719
• Rmse: 0.8197

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	13.2446	0.0	13.2446	3.6393
No log	2.0	2	11.4362	0.0021	11.4362	3.3817
No log	3.0	3	9.5547	0.0060	9.5547	3.0911
No log	4.0	4	8.7503	0.0016	8.7503	2.9581
No log	5.0	5	7.7381	0.0018	7.7381	2.7818
No log	6.0	6	7.0140	0.0	7.0140	2.6484
No log	7.0	7	6.4567	0.0042	6.4567	2.5410
No log	8.0	8	5.4971	0.0483	5.4971	2.3446
No log	9.0	9	4.6369	0.0223	4.6369	2.1534
No log	10.0	10	4.3683	0.0138	4.3683	2.0900
No log	11.0	11	3.5852	0.0079	3.5852	1.8935
No log	12.0	12	3.1347	0.0079	3.1347	1.7705
No log	13.0	13	2.7263	0.0106	2.7263	1.6512
No log	14.0	14	2.3806	0.0847	2.3806	1.5429
No log	15.0	15	2.1070	0.1145	2.1070	1.4516
No log	16.0	16	1.8036	0.1188	1.8036	1.3430
No log	17.0	17	1.6139	0.1014	1.6139	1.2704
No log	18.0	18	1.4148	0.0752	1.4148	1.1895
No log	19.0	19	1.2804	0.0533	1.2804	1.1315
No log	20.0	20	1.1611	0.0533	1.1611	1.0776
No log	21.0	21	1.1392	0.0558	1.1392	1.0673
No log	22.0	22	1.0178	0.0702	1.0178	1.0089
No log	23.0	23	0.8565	0.1831	0.8565	0.9255
No log	24.0	24	0.7860	0.3089	0.7860	0.8866
No log	25.0	25	0.7755	0.3556	0.7755	0.8806
No log	26.0	26	0.7226	0.3512	0.7226	0.8501
No log	27.0	27	0.6725	0.4256	0.6725	0.8201
No log	28.0	28	0.6478	0.4261	0.6478	0.8049
No log	29.0	29	0.6116	0.4414	0.6116	0.7820
No log	30.0	30	0.6005	0.4375	0.6005	0.7749
No log	31.0	31	0.5570	0.4587	0.5570	0.7463
No log	32.0	32	0.5856	0.4360	0.5856	0.7652
No log	33.0	33	0.5654	0.4562	0.5654	0.7519
No log	34.0	34	0.5219	0.5034	0.5219	0.7224
No log	35.0	35	0.5201	0.5120	0.5201	0.7212
No log	36.0	36	0.5484	0.5238	0.5484	0.7406
No log	37.0	37	0.6685	0.4591	0.6685	0.8176
No log	38.0	38	0.6781	0.4704	0.6781	0.8235
No log	39.0	39	0.5812	0.5903	0.5812	0.7623
No log	40.0	40	0.5474	0.6262	0.5474	0.7399
No log	41.0	41	0.5990	0.6062	0.5990	0.7739
No log	42.0	42	0.5749	0.6200	0.5749	0.7582
No log	43.0	43	0.5909	0.6394	0.5909	0.7687
No log	44.0	44	0.6623	0.6020	0.6623	0.8138
No log	45.0	45	0.6534	0.6180	0.6534	0.8083
No log	46.0	46	0.5828	0.6453	0.5828	0.7634
No log	47.0	47	0.5783	0.6449	0.5783	0.7605
No log	48.0	48	0.6225	0.6431	0.6225	0.7890
No log	49.0	49	0.6890	0.6252	0.6890	0.8300
No log	50.0	50	0.7343	0.6139	0.7343	0.8569
No log	51.0	51	0.6827	0.6411	0.6827	0.8263
No log	52.0	52	0.6242	0.6489	0.6242	0.7901
No log	53.0	53	0.6213	0.6446	0.6213	0.7882
No log	54.0	54	0.6411	0.6531	0.6411	0.8007
No log	55.0	55	0.6415	0.6574	0.6415	0.8009
No log	56.0	56	0.7086	0.6488	0.7086	0.8418
No log	57.0	57	0.8559	0.6070	0.8559	0.9252
No log	58.0	58	0.9021	0.5792	0.9021	0.9498
No log	59.0	59	0.8169	0.6250	0.8169	0.9038
No log	60.0	60	0.6882	0.6490	0.6882	0.8296
No log	61.0	61	0.5929	0.6704	0.5929	0.7700
No log	62.0	62	0.5792	0.6535	0.5792	0.7611
No log	63.0	63	0.5915	0.6706	0.5915	0.7691
No log	64.0	64	0.6637	0.6332	0.6637	0.8147
No log	65.0	65	0.8538	0.6013	0.8538	0.9240
No log	66.0	66	0.9702	0.5630	0.9702	0.9850
No log	67.0	67	0.9555	0.5706	0.9555	0.9775
No log	68.0	68	0.8559	0.5911	0.8559	0.9252
No log	69.0	69	0.7957	0.6084	0.7957	0.8920
No log	70.0	70	0.7509	0.6090	0.7509	0.8666
No log	71.0	71	0.7149	0.6160	0.7149	0.8455
No log	72.0	72	0.6953	0.6171	0.6953	0.8339
No log	73.0	73	0.7191	0.6172	0.7191	0.8480
No log	74.0	74	0.7576	0.6176	0.7576	0.8704
No log	75.0	75	0.7337	0.6240	0.7337	0.8566
No log	76.0	76	0.7655	0.6147	0.7655	0.8750
No log	77.0	77	0.7510	0.6175	0.7510	0.8666
No log	78.0	78	0.7301	0.6248	0.7301	0.8545
No log	79.0	79	0.7257	0.6189	0.7257	0.8519
No log	80.0	80	0.6754	0.6386	0.6754	0.8218
No log	81.0	81	0.6615	0.6397	0.6615	0.8133
No log	82.0	82	0.6753	0.6379	0.6753	0.8217
No log	83.0	83	0.6719	0.6355	0.6719	0.8197

Framework versions

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