ASAP_nosemanticV2_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold2

genki10/ASAP_nosemanticV2_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold2

ASAP_nosemanticV2_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold2 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

31% 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: Mar 8, 2025
Updated: Mar 8, 2025
SHA: 7da121e9

Try a prompt

Base models

Model card

From the Hugging Face model README

ASAP_nosemanticV2_FineTuningBERT_AugV12_k5_task1_organization_k5_k5_fold2

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: 0.8297
Qwk: 0.4537
Mse: 0.8292
Rmse: 0.9106

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	5	9.7639	0.0	9.7640	3.1247
No log	2.0	10	6.4009	0.0	6.4011	2.5300
No log	3.0	15	3.7472	0.0	3.7476	1.9359
No log	4.0	20	1.7524	0.0241	1.7529	1.3240
No log	5.0	25	1.7516	0.0334	1.7520	1.3236
No log	6.0	30	0.8923	0.0631	0.8926	0.9448
No log	7.0	35	1.5357	0.1181	1.5358	1.2393
No log	8.0	40	1.0086	0.3253	1.0082	1.0041
No log	9.0	45	2.5875	0.1028	2.5867	1.6083
No log	10.0	50	1.0688	0.3280	1.0674	1.0332
No log	11.0	55	1.8596	0.1936	1.8585	1.3633
No log	12.0	60	1.3326	0.2686	1.3315	1.1539
No log	13.0	65	1.1872	0.2942	1.1857	1.0889
No log	14.0	70	0.8770	0.4095	0.8757	0.9358
No log	15.0	75	1.0827	0.3777	1.0813	1.0399
No log	16.0	80	1.0256	0.4302	1.0245	1.0122
No log	17.0	85	1.1194	0.3977	1.1181	1.0574
No log	18.0	90	1.4674	0.3025	1.4659	1.2108
No log	19.0	95	0.8766	0.4557	0.8756	0.9357
No log	20.0	100	0.9448	0.4417	0.9438	0.9715
No log	21.0	105	1.2022	0.3466	1.2008	1.0958
No log	22.0	110	0.8712	0.4290	0.8705	0.9330
No log	23.0	115	0.9936	0.3899	0.9930	0.9965
No log	24.0	120	0.8311	0.4507	0.8307	0.9114
No log	25.0	125	0.7691	0.4675	0.7688	0.8768
No log	26.0	130	1.0095	0.3541	1.0087	1.0044
No log	27.0	135	0.9061	0.3651	0.9054	0.9515
No log	28.0	140	0.8850	0.3993	0.8843	0.9403
No log	29.0	145	0.7515	0.4953	0.7510	0.8666
No log	30.0	150	0.8684	0.4903	0.8678	0.9316
No log	31.0	155	1.2875	0.3317	1.2866	1.1343
No log	32.0	160	0.7633	0.4954	0.7628	0.8734
No log	33.0	165	0.8162	0.4548	0.8156	0.9031
No log	34.0	170	0.9062	0.4032	0.9056	0.9517
No log	35.0	175	0.9933	0.3755	0.9926	0.9963
No log	36.0	180	0.8328	0.4438	0.8321	0.9122
No log	37.0	185	0.7316	0.4730	0.7311	0.8551
No log	38.0	190	0.8193	0.4425	0.8188	0.9049
No log	39.0	195	0.8220	0.4245	0.8215	0.9064
No log	40.0	200	0.7515	0.4468	0.7510	0.8666
No log	41.0	205	0.8919	0.4071	0.8912	0.9440
No log	42.0	210	0.8082	0.4401	0.8076	0.8987
No log	43.0	215	0.8239	0.4291	0.8232	0.9073
No log	44.0	220	0.8377	0.4193	0.8371	0.9150
No log	45.0	225	0.7655	0.4845	0.7650	0.8746
No log	46.0	230	0.7442	0.4682	0.7437	0.8624
No log	47.0	235	1.0689	0.3639	1.0682	1.0335
No log	48.0	240	0.7543	0.4685	0.7539	0.8683
No log	49.0	245	0.8341	0.4575	0.8336	0.9130
No log	50.0	250	0.9112	0.4136	0.9108	0.9543
No log	51.0	255	0.7092	0.4780	0.7089	0.8420
No log	52.0	260	0.8297	0.4537	0.8292	0.9106

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 8, 2025
Updated: Mar 8, 2025