Version_weird_ASAP_FineTuningBERT_AugV12_k10_task1_organization_k10_k10_fold0

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: 0.5513
• Qwk: 0.6473
• Mse: 0.5513
• Rmse: 0.7425

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	3	8.2875	0.0	8.2875	2.8788
No log	2.0	6	6.8879	0.0	6.8879	2.6245
No log	3.0	9	5.9340	-0.0072	5.9340	2.4360
No log	4.0	12	4.5993	0.0077	4.5993	2.1446
No log	5.0	15	3.7118	0.0039	3.7118	1.9266
No log	6.0	18	2.6688	0.0	2.6688	1.6337
No log	7.0	21	1.8539	0.0382	1.8539	1.3616
No log	8.0	24	1.3065	0.0316	1.3065	1.1430
No log	9.0	27	0.9796	0.0106	0.9796	0.9898
No log	10.0	30	0.9040	0.0877	0.9040	0.9508
No log	11.0	33	0.7362	0.2206	0.7362	0.8580
No log	12.0	36	0.6894	0.1927	0.6894	0.8303
No log	13.0	39	0.6046	0.2739	0.6046	0.7776
No log	14.0	42	0.7324	0.2051	0.7324	0.8558
No log	15.0	45	0.8916	0.3889	0.8916	0.9443
No log	16.0	48	0.5338	0.3701	0.5338	0.7306
No log	17.0	51	0.5827	0.4515	0.5827	0.7633
No log	18.0	54	0.4980	0.5539	0.4980	0.7057
No log	19.0	57	0.7041	0.4755	0.7041	0.8391
No log	20.0	60	0.5295	0.6394	0.5295	0.7277
No log	21.0	63	0.6271	0.5941	0.6271	0.7919
No log	22.0	66	0.6143	0.6504	0.6143	0.7838
No log	23.0	69	0.7125	0.5701	0.7125	0.8441
No log	24.0	72	0.7605	0.5795	0.7605	0.8720
No log	25.0	75	0.6445	0.6149	0.6445	0.8028
No log	26.0	78	0.6498	0.5646	0.6498	0.8061
No log	27.0	81	0.8290	0.5526	0.8290	0.9105
No log	28.0	84	0.6493	0.5570	0.6493	0.8058
No log	29.0	87	0.5835	0.5850	0.5835	0.7639
No log	30.0	90	1.5530	0.4281	1.5530	1.2462
No log	31.0	93	1.8735	0.3682	1.8735	1.3687
No log	32.0	96	0.4996	0.6546	0.4996	0.7068
No log	33.0	99	0.6016	0.5979	0.6016	0.7757
No log	34.0	102	0.5630	0.6441	0.5630	0.7503
No log	35.0	105	0.5398	0.6289	0.5398	0.7347
No log	36.0	108	0.6251	0.5999	0.6251	0.7906
No log	37.0	111	0.4987	0.6472	0.4987	0.7062
No log	38.0	114	0.6891	0.5930	0.6891	0.8301
No log	39.0	117	0.5167	0.6225	0.5167	0.7188
No log	40.0	120	0.5475	0.6275	0.5475	0.7399
No log	41.0	123	0.6440	0.6200	0.6440	0.8025
No log	42.0	126	0.5500	0.6462	0.5500	0.7416
No log	43.0	129	0.5335	0.6448	0.5335	0.7304
No log	44.0	132	0.5434	0.6425	0.5434	0.7371
No log	45.0	135	0.6629	0.6258	0.6629	0.8142
No log	46.0	138	0.6554	0.6344	0.6554	0.8096
No log	47.0	141	0.6171	0.6328	0.6171	0.7856
No log	48.0	144	0.5426	0.6558	0.5426	0.7366
No log	49.0	147	0.7407	0.5876	0.7407	0.8606
No log	50.0	150	0.5936	0.6223	0.5936	0.7704
No log	51.0	153	0.5463	0.6463	0.5463	0.7392
No log	52.0	156	0.5558	0.6422	0.5558	0.7455
No log	53.0	159	0.6002	0.6409	0.6002	0.7748
No log	54.0	162	0.5889	0.6559	0.5889	0.7674
No log	55.0	165	0.5462	0.6438	0.5462	0.7391
No log	56.0	168	0.6099	0.6454	0.6099	0.7809
No log	57.0	171	0.5953	0.6443	0.5953	0.7715
No log	58.0	174	0.5372	0.6587	0.5372	0.7329
No log	59.0	177	0.6421	0.6247	0.6421	0.8013
No log	60.0	180	0.5899	0.6339	0.5899	0.7680
No log	61.0	183	0.5296	0.6402	0.5296	0.7278
No log	62.0	186	0.5654	0.6523	0.5654	0.7519
No log	63.0	189	0.6177	0.6275	0.6177	0.7860
No log	64.0	192	0.5536	0.6381	0.5536	0.7440
No log	65.0	195	0.5894	0.6267	0.5894	0.7677
No log	66.0	198	0.6442	0.6226	0.6442	0.8026
No log	67.0	201	0.5299	0.6341	0.5299	0.7279
No log	68.0	204	0.5615	0.6163	0.5615	0.7494
No log	69.0	207	0.5531	0.6237	0.5531	0.7437
No log	70.0	210	0.6036	0.6395	0.6036	0.7769
No log	71.0	213	0.6000	0.6364	0.6000	0.7746
No log	72.0	216	0.5330	0.6481	0.5330	0.7301
No log	73.0	219	0.5289	0.6393	0.5289	0.7272
No log	74.0	222	0.5677	0.6474	0.5677	0.7535
No log	75.0	225	0.6284	0.6242	0.6284	0.7927
No log	76.0	228	0.5750	0.6426	0.5750	0.7583
No log	77.0	231	0.5536	0.6448	0.5536	0.7441
No log	78.0	234	0.5513	0.6473	0.5513	0.7425

Framework versions

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