Version12AGAINNNASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold0

genki10/Version12AGAINNNASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_fold0

Version12AGAINNNASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_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

34% of all-time downloads

All-time downloads

Public

Repo size

21.9 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: Mar 9, 2025
Updated: Mar 9, 2025
SHA: 7accbe0d

Try a prompt

Base models

Model card

From the Hugging Face model README

Version12AGAINNNASAP_FineTuningBERT_AugV12_k15_task1_organization_k15_k15_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: 0.4987
Qwk: 0.6454
Mse: 0.4987
Rmse: 0.7062

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	8.1956	0.0	8.1956	2.8628
No log	2.0	6	6.9316	0.0	6.9316	2.6328
No log	3.0	9	5.7383	0.0129	5.7383	2.3955
No log	4.0	12	4.5410	0.0039	4.5410	2.1310
No log	5.0	15	3.4243	0.0	3.4243	1.8505
No log	6.0	18	2.4243	0.0764	2.4243	1.5570
No log	7.0	21	1.6122	0.0316	1.6122	1.2697
No log	8.0	24	1.1316	0.0106	1.1316	1.0637
No log	9.0	27	0.8494	0.3258	0.8494	0.9216
No log	10.0	30	0.7781	0.0968	0.7781	0.8821
No log	11.0	33	0.8229	0.0521	0.8229	0.9072
No log	12.0	36	0.9938	0.0521	0.9938	0.9969
No log	13.0	39	1.1787	0.2423	1.1787	1.0857
No log	14.0	42	1.3687	0.1768	1.3687	1.1699
No log	15.0	45	1.0668	0.3510	1.0668	1.0328
No log	16.0	48	0.6477	0.4793	0.6477	0.8048
No log	17.0	51	0.5008	0.6081	0.5008	0.7077
No log	18.0	54	0.5441	0.6545	0.5441	0.7377
No log	19.0	57	0.5146	0.6376	0.5146	0.7173
No log	20.0	60	0.4834	0.6531	0.4834	0.6953
No log	21.0	63	0.5371	0.6471	0.5371	0.7329
No log	22.0	66	0.5001	0.6699	0.5001	0.7072
No log	23.0	69	1.2744	0.4948	1.2744	1.1289
No log	24.0	72	0.5730	0.6343	0.5730	0.7570
No log	25.0	75	0.9316	0.5431	0.9316	0.9652
No log	26.0	78	0.5195	0.6302	0.5195	0.7207
No log	27.0	81	0.6441	0.6208	0.6441	0.8026
No log	28.0	84	0.4729	0.6384	0.4729	0.6876
No log	29.0	87	0.5504	0.6364	0.5504	0.7419
No log	30.0	90	0.5440	0.6326	0.5440	0.7375
No log	31.0	93	0.4887	0.6219	0.4887	0.6991
No log	32.0	96	0.5220	0.6438	0.5220	0.7225
No log	33.0	99	0.4803	0.6451	0.4803	0.6930
No log	34.0	102	0.6905	0.5969	0.6905	0.8309
No log	35.0	105	0.5435	0.6502	0.5435	0.7372
No log	36.0	108	0.5062	0.6603	0.5062	0.7115
No log	37.0	111	0.5863	0.6488	0.5863	0.7657
No log	38.0	114	0.4874	0.6529	0.4874	0.6981
No log	39.0	117	0.5749	0.6443	0.5749	0.7582
No log	40.0	120	0.4754	0.6483	0.4754	0.6895
No log	41.0	123	0.7331	0.5950	0.7331	0.8562
No log	42.0	126	0.4987	0.6454	0.4987	0.7062

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: Mar 9, 2025
Updated: Mar 9, 2025