ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold1

genki10/ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold1

ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold1 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

43% of all-time downloads

All-time downloads

Public

Repo size

16.2 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: Feb 13, 2025
Updated: Feb 13, 2025
SHA: 6b6a6e3e

Try a prompt

Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV10_k5_task1_organization_k5_k5_fold1

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: 0.9997
Qwk: 0.3173
Mse: 0.9984
Rmse: 0.9992

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	4	8.4310	0.0	8.4282	2.9031
No log	2.0	8	4.3097	0.0244	4.3076	2.0755
No log	3.0	12	2.7468	0.0244	2.7451	1.6568
No log	4.0	16	1.6353	0.0676	1.6337	1.2781
No log	5.0	20	1.4390	0.0145	1.4376	1.1990
No log	6.0	24	1.0699	-0.0154	1.0686	1.0337
No log	7.0	28	1.2028	-0.0607	1.2015	1.0962
No log	8.0	32	1.0608	0.0612	1.0595	1.0293
No log	9.0	36	0.8281	0.2207	0.8269	0.9093
No log	10.0	40	1.5832	-0.1725	1.5814	1.2575
No log	11.0	44	0.7564	0.2205	0.7552	0.8690
No log	12.0	48	1.7130	-0.0358	1.7109	1.3080
No log	13.0	52	0.7539	0.2884	0.7525	0.8674
No log	14.0	56	1.2553	0.0807	1.2535	1.1196
No log	15.0	60	0.7780	0.2804	0.7766	0.8813
No log	16.0	64	1.1622	0.1353	1.1604	1.0772
No log	17.0	68	1.1632	0.1604	1.1612	1.0776
No log	18.0	72	1.2001	0.1513	1.1980	1.0945
No log	19.0	76	1.2297	0.1296	1.2276	1.1080
No log	20.0	80	1.4290	0.0899	1.4268	1.1945
No log	21.0	84	1.2885	0.1333	1.2866	1.1343
No log	22.0	88	1.1619	0.2241	1.1602	1.0771
No log	23.0	92	1.0291	0.3353	1.0278	1.0138
No log	24.0	96	1.0539	0.2838	1.0523	1.0258
No log	25.0	100	1.0496	0.2612	1.0479	1.0237
No log	26.0	104	1.4310	0.1004	1.4288	1.1953
No log	27.0	108	1.1002	0.2325	1.0985	1.0481
No log	28.0	112	1.0199	0.2808	1.0182	1.0091
No log	29.0	116	1.3163	0.1453	1.3143	1.1464
No log	30.0	120	1.2588	0.1399	1.2570	1.1211
No log	31.0	124	1.1965	0.1625	1.1948	1.0931
No log	32.0	128	1.2929	0.1622	1.2910	1.1362
No log	33.0	132	1.0807	0.2641	1.0792	1.0388
No log	34.0	136	1.4256	0.0699	1.4236	1.1931
No log	35.0	140	1.0524	0.2835	1.0509	1.0251
No log	36.0	144	1.2015	0.2124	1.1998	1.0954
No log	37.0	148	1.3696	0.1113	1.3678	1.1695
No log	38.0	152	1.0186	0.2879	1.0172	1.0086
No log	39.0	156	1.2898	0.1304	1.2880	1.1349
No log	40.0	160	1.1203	0.1776	1.1187	1.0577
No log	41.0	164	1.1409	0.1996	1.1393	1.0674
No log	42.0	168	1.1281	0.2277	1.1264	1.0613
No log	43.0	172	0.9997	0.3173	0.9984	0.9992

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 13, 2025
Updated: Feb 13, 2025