ASAP_FineTuningBERT_AugV10_k3_task1_organization_k3_k3_fold1

genki10/ASAP_FineTuningBERT_AugV10_k3_task1_organization_k3_k3_fold1

ASAP_FineTuningBERT_AugV10_k3_task1_organization_k3_k3_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. --

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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 13, 2025
SHA: 9998fd5d

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Base models

Model card

From the Hugging Face model README

ASAP_FineTuningBERT_AugV10_k3_task1_organization_k3_k3_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: 0.9206
Qwk: 0.3681
Mse: 0.9187
Rmse: 0.9585

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	3	7.9409	0.0	7.9383	2.8175
No log	2.0	6	6.0692	-0.0016	6.0669	2.4631
No log	3.0	9	4.1457	0.0	4.1435	2.0356
No log	4.0	12	2.9806	0.0	2.9787	1.7259
No log	5.0	15	2.2070	0.1676	2.2053	1.4850
No log	6.0	18	1.5578	0.0262	1.5563	1.2475
No log	7.0	21	1.3587	0.0	1.3573	1.1650
No log	8.0	24	1.2643	0.0	1.2628	1.1237
No log	9.0	27	1.1955	0.0	1.1944	1.0929
No log	10.0	30	1.2384	0.0	1.2368	1.1121
No log	11.0	33	1.1696	0.0	1.1680	1.0807
No log	12.0	36	1.0530	0.0379	1.0516	1.0255
No log	13.0	39	1.2803	0.1521	1.2785	1.1307
No log	14.0	42	0.8747	0.3030	0.8736	0.9347
No log	15.0	45	0.9714	0.2764	0.9695	0.9847
No log	16.0	48	0.7334	0.3662	0.7320	0.8555
No log	17.0	51	0.8459	0.3343	0.8439	0.9186
No log	18.0	54	0.8321	0.3992	0.8300	0.9110
No log	19.0	57	0.7656	0.4505	0.7636	0.8738
No log	20.0	60	1.2861	0.2816	1.2834	1.1329
No log	21.0	63	0.8671	0.3649	0.8649	0.9300
No log	22.0	66	0.8727	0.3884	0.8704	0.9330
No log	23.0	69	1.2339	0.2708	1.2308	1.1094
No log	24.0	72	0.8241	0.3482	0.8224	0.9069
No log	25.0	75	1.0730	0.2724	1.0704	1.0346
No log	26.0	78	0.9177	0.3427	0.9154	0.9568
No log	27.0	81	0.9576	0.3641	0.9552	0.9774
No log	28.0	84	1.0549	0.2987	1.0526	1.0260
No log	29.0	87	0.7221	0.4297	0.7206	0.8489
No log	30.0	90	1.0069	0.3088	1.0049	1.0024
No log	31.0	93	0.8443	0.3769	0.8424	0.9178
No log	32.0	96	1.0111	0.2867	1.0089	1.0045
No log	33.0	99	0.9372	0.3002	0.9352	0.9671
No log	34.0	102	0.8734	0.3725	0.8716	0.9336
No log	35.0	105	0.9518	0.3615	0.9498	0.9746
No log	36.0	108	0.8249	0.4102	0.8232	0.9073
No log	37.0	111	0.9089	0.3643	0.9069	0.9523
No log	38.0	114	0.7877	0.4136	0.7861	0.8866
No log	39.0	117	0.9206	0.3681	0.9187	0.9585

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 13, 2025