ASAP_FineTuningBERT_AugV14_k3_task1_organization_k3_k3_fold3

genki10/ASAP_FineTuningBERT_AugV14_k3_task1_organization_k3_k3_fold3

ASAP_FineTuningBERT_AugV14_k3_task1_organization_k3_k3_fold3 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Feb 20, 2025
Updated: Feb 20, 2025
SHA: 43c6b245

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV14_k3_task1_organization_k3_k3_fold3

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: 0.8429
Qwk: 0.4833
Mse: 0.8436
Rmse: 0.9185

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	6	10.4258	0.0018	10.4240	3.2286
No log	2.0	12	5.9119	0.0535	5.9106	2.4312
No log	3.0	18	2.8483	0.0070	2.8474	1.6874
No log	4.0	24	1.5017	0.0184	1.5010	1.2252
No log	5.0	30	0.9558	0.1709	0.9553	0.9774
No log	6.0	36	1.1057	0.0045	1.1050	1.0512
No log	7.0	42	0.8222	0.3312	0.8220	0.9066
No log	8.0	48	0.7980	0.3441	0.7978	0.8932
No log	9.0	54	1.3357	0.2401	1.3358	1.1557
No log	10.0	60	1.3153	0.2111	1.3154	1.1469
No log	11.0	66	0.6148	0.5136	0.6152	0.7844
No log	12.0	72	0.7137	0.4656	0.7142	0.8451
No log	13.0	78	0.9295	0.3852	0.9300	0.9644
No log	14.0	84	0.8061	0.4200	0.8067	0.8982
No log	15.0	90	0.9550	0.3781	0.9557	0.9776
No log	16.0	96	0.7296	0.4956	0.7304	0.8546
No log	17.0	102	0.9185	0.4452	0.9196	0.9590
No log	18.0	108	1.0047	0.4111	1.0058	1.0029
No log	19.0	114	1.0263	0.4102	1.0274	1.0136
No log	20.0	120	1.0994	0.3804	1.1005	1.0490
No log	21.0	126	1.0282	0.3866	1.0292	1.0145
No log	22.0	132	0.9537	0.4377	0.9546	0.9771
No log	23.0	138	0.9081	0.4989	0.9089	0.9534
No log	24.0	144	0.9570	0.4439	0.9580	0.9788
No log	25.0	150	1.0973	0.3881	1.0984	1.0481
No log	26.0	156	0.8395	0.5147	0.8403	0.9167
No log	27.0	162	0.9046	0.4505	0.9056	0.9516
No log	28.0	168	1.1607	0.3744	1.1617	1.0778
No log	29.0	174	1.3324	0.3184	1.3333	1.1547
No log	30.0	180	0.7371	0.5318	0.7376	0.8588
No log	31.0	186	1.2841	0.3139	1.2852	1.1337
No log	32.0	192	0.7931	0.5180	0.7939	0.8910
No log	33.0	198	0.8102	0.5045	0.8110	0.9006
No log	34.0	204	1.0949	0.3563	1.0959	1.0469
No log	35.0	210	0.7398	0.5198	0.7405	0.8605
No log	36.0	216	0.7911	0.5196	0.7919	0.8899
No log	37.0	222	1.0472	0.4183	1.0484	1.0239
No log	38.0	228	0.9603	0.4373	0.9612	0.9804
No log	39.0	234	0.9077	0.4492	0.9086	0.9532
No log	40.0	240	1.0537	0.3881	1.0548	1.0270
No log	41.0	246	0.7232	0.5402	0.7239	0.8508
No log	42.0	252	0.9110	0.4468	0.9120	0.9550
No log	43.0	258	0.9335	0.4522	0.9346	0.9668
No log	44.0	264	0.7840	0.5177	0.7848	0.8859
No log	45.0	270	0.7803	0.5339	0.7811	0.8838
No log	46.0	276	0.8556	0.4812	0.8566	0.9255
No log	47.0	282	0.9978	0.4284	0.9987	0.9994
No log	48.0	288	1.0046	0.4172	1.0055	1.0027
No log	49.0	294	0.8930	0.4490	0.8939	0.9455
No log	50.0	300	0.7624	0.5161	0.7630	0.8735
No log	51.0	306	1.0170	0.3818	1.0178	1.0089
No log	52.0	312	0.8540	0.4625	0.8548	0.9246
No log	53.0	318	0.8037	0.4874	0.8044	0.8969
No log	54.0	324	0.8473	0.4576	0.8481	0.9209
No log	55.0	330	0.8753	0.4682	0.8762	0.9361
No log	56.0	336	0.8218	0.4568	0.8226	0.9070
No log	57.0	342	0.7810	0.4925	0.7817	0.8841
No log	58.0	348	0.8258	0.4778	0.8266	0.9092
No log	59.0	354	0.7983	0.4942	0.7990	0.8939
No log	60.0	360	0.8193	0.4887	0.8201	0.9056
No log	61.0	366	0.8429	0.4833	0.8436	0.9185

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Feb 20, 2025
Updated: Feb 20, 2025