ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold4

genki10/ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold4

ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold4 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

48% of all-time downloads

All-time downloads

Public

Repo size

30.2 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 10, 2025
Updated: Feb 11, 2025
SHA: ffb96f34

Try a prompt

Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV6_k15_task1_organization_k15_k15_fold4

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: 0.6343
Qwk: 0.5365
Mse: 0.6343
Rmse: 0.7964

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	12	4.4883	0.0079	4.4883	2.1186
No log	2.0	24	1.2805	0.0316	1.2805	1.1316
No log	3.0	36	1.8149	0.1620	1.8149	1.3472
No log	4.0	48	2.3422	0.0898	2.3422	1.5304
No log	5.0	60	1.4298	0.2580	1.4298	1.1958
No log	6.0	72	0.7745	0.4577	0.7745	0.8801
No log	7.0	84	0.6842	0.5272	0.6842	0.8272
No log	8.0	96	1.0064	0.4099	1.0064	1.0032
No log	9.0	108	1.3106	0.3335	1.3106	1.1448
No log	10.0	120	0.9229	0.4795	0.9229	0.9607
No log	11.0	132	0.9327	0.4457	0.9327	0.9657
No log	12.0	144	1.1690	0.3503	1.1690	1.0812
No log	13.0	156	0.7106	0.5078	0.7106	0.8430
No log	14.0	168	0.6853	0.5637	0.6853	0.8278
No log	15.0	180	0.7130	0.5424	0.7130	0.8444
No log	16.0	192	0.9954	0.4091	0.9954	0.9977
No log	17.0	204	0.6456	0.5220	0.6456	0.8035
No log	18.0	216	0.7522	0.4888	0.7522	0.8673
No log	19.0	228	0.6758	0.5690	0.6758	0.8221
No log	20.0	240	0.6731	0.4959	0.6731	0.8205
No log	21.0	252	0.7830	0.4645	0.7830	0.8849
No log	22.0	264	1.0716	0.3954	1.0716	1.0352
No log	23.0	276	0.8342	0.4371	0.8342	0.9134
No log	24.0	288	0.6690	0.5403	0.6690	0.8179
No log	25.0	300	0.9242	0.4374	0.9242	0.9614
No log	26.0	312	0.8776	0.4297	0.8776	0.9368
No log	27.0	324	0.6761	0.5031	0.6761	0.8223
No log	28.0	336	0.6798	0.4976	0.6798	0.8245
No log	29.0	348	0.8992	0.4341	0.8992	0.9482
No log	30.0	360	0.6380	0.5408	0.6380	0.7987
No log	31.0	372	0.6170	0.5646	0.6170	0.7855
No log	32.0	384	0.6850	0.5264	0.6850	0.8276
No log	33.0	396	0.6408	0.5488	0.6408	0.8005
No log	34.0	408	0.7219	0.4660	0.7219	0.8496
No log	35.0	420	0.6105	0.5520	0.6105	0.7813
No log	36.0	432	0.7713	0.4795	0.7713	0.8782
No log	37.0	444	0.7516	0.4829	0.7516	0.8670
No log	38.0	456	0.6130	0.5617	0.6130	0.7829
No log	39.0	468	0.6343	0.5365	0.6343	0.7964

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 10, 2025
Updated: Feb 11, 2025