Trial2BERT_AugV8_k3_task1_organization_sp010_lw070_fold0

genki10/Trial2BERT_AugV8_k3_task1_organization_sp010_lw070_fold0

Trial2BERT_AugV8_k3_task1_organization_sp010_lw070_fold0 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. --

Downloads · 30 days

35% of all-time downloads

All-time downloads

Public

Repo size

28.5 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin876 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Apr 5, 2025
Updated: Apr 5, 2025
SHA: 03c30413

Try a prompt

Base models

Model card

From the Hugging Face model README

Trial2BERT_AugV8_k3_task1_organization_sp010_lw070_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: 0.8127
Qwk: 0.3286
Mse: 0.8127
Rmse: 0.9015

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: 150

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	1.0	3	8.0947	0.0	8.0947	2.8451
No log	2.0	6	6.6651	0.0	6.6651	2.5817
No log	3.0	9	5.3609	0.0115	5.3609	2.3154
No log	4.0	12	4.0881	0.0039	4.0881	2.0219
No log	5.0	15	2.8711	0.0	2.8711	1.6944
No log	6.0	18	1.9175	0.0601	1.9175	1.3847
No log	7.0	21	1.3622	0.0316	1.3622	1.1671
No log	8.0	24	1.1759	0.0382	1.1759	1.0844
No log	9.0	27	1.7527	0.1484	1.7527	1.3239
No log	10.0	30	1.0934	0.0664	1.0934	1.0456
No log	11.0	33	1.0539	0.0751	1.0539	1.0266
No log	12.0	36	1.6176	0.1629	1.6176	1.2718
No log	13.0	39	0.9154	0.2189	0.9154	0.9568
No log	14.0	42	1.4584	0.1744	1.4584	1.2077
No log	15.0	45	0.7646	0.3008	0.7646	0.8744
No log	16.0	48	1.2107	0.2332	1.2107	1.1003
No log	17.0	51	0.6826	0.2886	0.6826	0.8262
No log	18.0	54	0.6861	0.3398	0.6861	0.8283
No log	19.0	57	1.0245	0.2738	1.0245	1.0122
No log	20.0	60	0.7204	0.2902	0.7204	0.8488
No log	21.0	63	0.6517	0.3502	0.6517	0.8073
No log	22.0	66	1.2933	0.2288	1.2933	1.1372
No log	23.0	69	0.7810	0.3520	0.7810	0.8837
No log	24.0	72	0.9822	0.3476	0.9822	0.9911
No log	25.0	75	0.8889	0.3586	0.8889	0.9428
No log	26.0	78	1.1795	0.2579	1.1795	1.0861
No log	27.0	81	0.8352	0.3586	0.8352	0.9139
No log	28.0	84	1.0359	0.2822	1.0359	1.0178
No log	29.0	87	1.0761	0.2811	1.0761	1.0373
No log	30.0	90	0.9561	0.3423	0.9561	0.9778
No log	31.0	93	1.2023	0.2403	1.2023	1.0965
No log	32.0	96	0.7997	0.3735	0.7997	0.8942
No log	33.0	99	1.3016	0.2084	1.3016	1.1409
No log	34.0	102	0.8598	0.2975	0.8598	0.9273
No log	35.0	105	0.9769	0.3001	0.9769	0.9884
No log	36.0	108	0.9237	0.3468	0.9237	0.9611
No log	37.0	111	0.9286	0.3710	0.9286	0.9636
No log	38.0	114	0.8659	0.3598	0.8659	0.9306
No log	39.0	117	0.9041	0.2894	0.9041	0.9508
No log	40.0	120	0.9891	0.2689	0.9891	0.9945
No log	41.0	123	0.8804	0.3592	0.8804	0.9383
No log	42.0	126	1.0012	0.2801	1.0012	1.0006
No log	43.0	129	0.8234	0.4105	0.8234	0.9074
No log	44.0	132	0.9405	0.2847	0.9405	0.9698
No log	45.0	135	0.8492	0.3437	0.8492	0.9215
No log	46.0	138	1.0038	0.2437	1.0038	1.0019
No log	47.0	141	0.8665	0.2946	0.8665	0.9309
No log	48.0	144	0.9276	0.2801	0.9276	0.9631
No log	49.0	147	0.9182	0.2880	0.9182	0.9582
No log	50.0	150	0.9029	0.3052	0.9029	0.9502
No log	51.0	153	0.8742	0.2999	0.8742	0.9350
No log	52.0	156	0.9399	0.2755	0.9399	0.9695
No log	53.0	159	1.0476	0.2502	1.0476	1.0235
No log	54.0	162	0.8787	0.3845	0.8787	0.9374
No log	55.0	165	1.0020	0.2662	1.0020	1.0010
No log	56.0	168	0.8006	0.3764	0.8006	0.8948
No log	57.0	171	0.9652	0.2535	0.9652	0.9825
No log	58.0	174	0.8127	0.3286	0.8127	0.9015

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Apr 5, 2025
Updated: Apr 5, 2025