ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold0

genki10/ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_fold0

ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_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. --

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Feb 12, 2025
Updated: Feb 12, 2025
SHA: 21a4c637

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV9_k5_task1_organization_k5_k5_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: 0.7451
Qwk: 0.4419
Mse: 0.7451
Rmse: 0.8632

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	8.3650	0.0036	8.3650	2.8922
No log	2.0	8	5.2803	0.0139	5.2803	2.2979
No log	3.0	12	3.3764	0.0077	3.3764	1.8375
No log	4.0	16	2.1275	0.0556	2.1275	1.4586
No log	5.0	20	1.3581	0.0316	1.3581	1.1654
No log	6.0	24	1.3131	0.0316	1.3131	1.1459
No log	7.0	28	1.2524	0.0575	1.2524	1.1191
No log	8.0	32	1.0017	0.0484	1.0017	1.0009
No log	9.0	36	0.9523	0.2237	0.9523	0.9759
No log	10.0	40	0.8912	0.2868	0.8912	0.9440
No log	11.0	44	0.7514	0.2965	0.7514	0.8668
No log	12.0	48	0.7690	0.2304	0.7690	0.8769
No log	13.0	52	0.8197	0.2657	0.8197	0.9054
No log	14.0	56	0.6791	0.2583	0.6791	0.8241
No log	15.0	60	0.7078	0.2622	0.7078	0.8413
No log	16.0	64	0.8696	0.2963	0.8696	0.9325
No log	17.0	68	0.7230	0.2956	0.7230	0.8503
No log	18.0	72	0.7447	0.3287	0.7447	0.8630
No log	19.0	76	0.7390	0.3794	0.7390	0.8597
No log	20.0	80	0.8023	0.3805	0.8023	0.8957
No log	21.0	84	0.7123	0.4308	0.7123	0.8440
No log	22.0	88	0.8262	0.3869	0.8262	0.9090
No log	23.0	92	0.9144	0.2445	0.9144	0.9563
No log	24.0	96	0.8350	0.3755	0.8350	0.9138
No log	25.0	100	1.1399	0.3128	1.1399	1.0677
No log	26.0	104	0.8003	0.4442	0.8003	0.8946
No log	27.0	108	0.8016	0.3920	0.8016	0.8953
No log	28.0	112	0.9623	0.3177	0.9623	0.9809
No log	29.0	116	0.7674	0.4617	0.7674	0.8760
No log	30.0	120	0.7989	0.4737	0.7989	0.8938
No log	31.0	124	0.8570	0.4053	0.8570	0.9257
No log	32.0	128	0.7653	0.4721	0.7653	0.8748
No log	33.0	132	0.7658	0.4218	0.7658	0.8751
No log	34.0	136	0.8837	0.3677	0.8837	0.9401
No log	35.0	140	0.8085	0.4143	0.8085	0.8992
No log	36.0	144	0.7826	0.4673	0.7826	0.8846
No log	37.0	148	0.8011	0.4286	0.8011	0.8950
No log	38.0	152	0.9135	0.3545	0.9135	0.9558
No log	39.0	156	0.7703	0.5010	0.7703	0.8776
No log	40.0	160	0.8248	0.3967	0.8248	0.9082
No log	41.0	164	0.7986	0.4865	0.7986	0.8936
No log	42.0	168	0.7987	0.4763	0.7987	0.8937
No log	43.0	172	0.7613	0.4566	0.7613	0.8725
No log	44.0	176	0.8048	0.4222	0.8048	0.8971
No log	45.0	180	0.8134	0.4429	0.8134	0.9019
No log	46.0	184	0.8232	0.4106	0.8232	0.9073
No log	47.0	188	0.7851	0.4477	0.7851	0.8860
No log	48.0	192	0.7467	0.4565	0.7467	0.8641
No log	49.0	196	0.7421	0.4295	0.7421	0.8614
No log	50.0	200	0.7706	0.4304	0.7706	0.8778
No log	51.0	204	0.6962	0.4846	0.6962	0.8344
No log	52.0	208	0.7239	0.4406	0.7239	0.8508
No log	53.0	212	0.7562	0.4838	0.7562	0.8696
No log	54.0	216	0.7933	0.4603	0.7933	0.8907
No log	55.0	220	0.7551	0.4913	0.7551	0.8690
No log	56.0	224	0.7132	0.4790	0.7132	0.8445
No log	57.0	228	0.7516	0.4342	0.7516	0.8670
No log	58.0	232	0.8262	0.4475	0.8262	0.9090
No log	59.0	236	0.7451	0.4419	0.7451	0.8632

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 12, 2025
Updated: Feb 12, 2025