ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold2

genki10/ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold2

ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_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. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Feb 10, 2025
Updated: Feb 10, 2025
SHA: 8972db6e

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_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: 0.8115
Qwk: 0.5389
Mse: 0.8113
Rmse: 0.9007

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	2	8.5519	0.0	8.5519	2.9244
No log	2.0	4	7.5631	0.0	7.5630	2.7501
No log	3.0	6	5.5187	0.0274	5.5190	2.3493
No log	4.0	8	4.3909	0.0021	4.3912	2.0955
No log	5.0	10	3.6105	0.0	3.6109	1.9002
No log	6.0	12	2.9071	0.0	2.9076	1.7052
No log	7.0	14	2.3574	0.1532	2.3578	1.5355
No log	8.0	16	1.7874	0.0513	1.7879	1.3371
No log	9.0	18	1.4958	0.0107	1.4962	1.2232
No log	10.0	20	1.2566	0.0174	1.2570	1.1212
No log	11.0	22	1.1536	0.0241	1.1540	1.0742
No log	12.0	24	0.9378	0.0241	0.9381	0.9686
No log	13.0	26	0.9670	0.0675	0.9673	0.9835
No log	14.0	28	0.8263	0.1924	0.8266	0.9092
No log	15.0	30	0.7103	0.4755	0.7105	0.8429
No log	16.0	32	0.6676	0.5139	0.6678	0.8172
No log	17.0	34	0.7780	0.3938	0.7783	0.8822
No log	18.0	36	0.6317	0.5112	0.6319	0.7949
No log	19.0	38	0.6345	0.4191	0.6348	0.7967
No log	20.0	40	0.6324	0.4265	0.6327	0.7954
No log	21.0	42	0.5278	0.5176	0.5279	0.7266
No log	22.0	44	0.5252	0.5193	0.5253	0.7248
No log	23.0	46	0.5544	0.5146	0.5546	0.7447
No log	24.0	48	0.4996	0.5381	0.4997	0.7069
No log	25.0	50	0.5768	0.4211	0.5768	0.7594
No log	26.0	52	0.6794	0.3153	0.6794	0.8243
No log	27.0	54	0.7192	0.3181	0.7192	0.8481
No log	28.0	56	0.6061	0.5317	0.6059	0.7784
No log	29.0	58	0.5439	0.5610	0.5437	0.7374
No log	30.0	60	0.5292	0.5778	0.5290	0.7273
No log	31.0	62	0.5194	0.5994	0.5191	0.7205
No log	32.0	64	0.6234	0.5649	0.6232	0.7895
No log	33.0	66	0.7518	0.4805	0.7518	0.8671
No log	34.0	68	0.8477	0.4093	0.8476	0.9207
No log	35.0	70	0.7694	0.4810	0.7694	0.8771
No log	36.0	72	0.7291	0.4392	0.7290	0.8538
No log	37.0	74	0.6280	0.5406	0.6278	0.7924
No log	38.0	76	0.6775	0.5402	0.6773	0.8230
No log	39.0	78	0.6848	0.5351	0.6848	0.8275
No log	40.0	80	0.6457	0.5156	0.6457	0.8036
No log	41.0	82	0.6055	0.5368	0.6055	0.7781
No log	42.0	84	0.6156	0.5713	0.6156	0.7846
No log	43.0	86	0.5711	0.5485	0.5711	0.7557
No log	44.0	88	0.6018	0.5687	0.6018	0.7757
No log	45.0	90	0.6342	0.5730	0.6341	0.7963
No log	46.0	92	0.6291	0.5693	0.6291	0.7932
No log	47.0	94	0.6519	0.5675	0.6519	0.8074
No log	48.0	96	0.7210	0.5504	0.7209	0.8490
No log	49.0	98	0.6731	0.5398	0.6731	0.8204
No log	50.0	100	0.6817	0.5328	0.6817	0.8257
No log	51.0	102	0.8115	0.5389	0.8113	0.9007

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 10, 2025