Version22NewTestASAP_FineTuningBERT_AugV22_k15_task1_organization_k15_k15_fold0

genki10/Version22NewTestASAP_FineTuningBERT_AugV22_k15_task1_organization_k15_k15_fold0

Version22NewTestASAP_FineTuningBERT_AugV22_k15_task1_organization_k15_k15_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: Mar 16, 2025
Updated: Mar 16, 2025
SHA: 7edbfbdf

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Base models

Model card

From the Hugging Face model README

Version22NewTestASAP_FineTuningBERT_AugV22_k15_task1_organization_k15_k15_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: 0.8640
Qwk: 0.3560
Mse: 0.8640
Rmse: 0.9295

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	8	5.9415	0.0230	5.9415	2.4375
No log	2.0	16	2.7340	0.0	2.7340	1.6535
No log	3.0	24	1.1272	0.0316	1.1272	1.0617
No log	4.0	32	1.2920	0.0575	1.2920	1.1367
No log	5.0	40	0.8877	0.3081	0.8877	0.9422
No log	6.0	48	1.8879	0.1080	1.8879	1.3740
No log	7.0	56	1.9509	0.1221	1.9509	1.3968
No log	8.0	64	2.3226	0.0580	2.3226	1.5240
No log	9.0	72	2.2896	0.0909	2.2896	1.5132
No log	10.0	80	1.6772	0.1220	1.6772	1.2951
No log	11.0	88	1.8565	0.1005	1.8565	1.3625
No log	12.0	96	1.5372	0.1301	1.5372	1.2398
No log	13.0	104	1.9643	0.0718	1.9643	1.4015
No log	14.0	112	2.1979	0.0612	2.1979	1.4825
No log	15.0	120	1.5771	0.1532	1.5771	1.2558
No log	16.0	128	1.1618	0.2362	1.1618	1.0779
No log	17.0	136	0.9511	0.2473	0.9511	0.9753
No log	18.0	144	1.1355	0.2651	1.1355	1.0656
No log	19.0	152	1.2503	0.2244	1.2503	1.1182
No log	20.0	160	1.2729	0.2316	1.2729	1.1282
No log	21.0	168	0.8787	0.3371	0.8787	0.9374
No log	22.0	176	1.1748	0.2477	1.1748	1.0839
No log	23.0	184	1.2370	0.2252	1.2370	1.1122
No log	24.0	192	1.0311	0.3250	1.0311	1.0154
No log	25.0	200	1.0513	0.2864	1.0513	1.0253
No log	26.0	208	1.3348	0.2256	1.3348	1.1553
No log	27.0	216	1.0132	0.2804	1.0132	1.0066
No log	28.0	224	1.0568	0.2886	1.0568	1.0280
No log	29.0	232	1.0327	0.3298	1.0327	1.0162
No log	30.0	240	1.1607	0.2984	1.1607	1.0774
No log	31.0	248	1.1535	0.2740	1.1535	1.0740
No log	32.0	256	0.8700	0.3704	0.8700	0.9327
No log	33.0	264	1.1213	0.3191	1.1213	1.0589
No log	34.0	272	1.2208	0.3151	1.2208	1.1049
No log	35.0	280	1.2291	0.2937	1.2291	1.1086
No log	36.0	288	1.0121	0.3667	1.0121	1.0060
No log	37.0	296	0.9605	0.3769	0.9605	0.9801
No log	38.0	304	0.8592	0.4027	0.8592	0.9269
No log	39.0	312	0.8798	0.3576	0.8798	0.9380
No log	40.0	320	1.0110	0.3279	1.0110	1.0055
No log	41.0	328	1.1666	0.2769	1.1666	1.0801
No log	42.0	336	1.1076	0.2859	1.1076	1.0524
No log	43.0	344	1.1940	0.2831	1.1940	1.0927
No log	44.0	352	0.9909	0.3542	0.9909	0.9954
No log	45.0	360	0.8445	0.3686	0.8445	0.9190
No log	46.0	368	1.0505	0.2956	1.0505	1.0249
No log	47.0	376	1.1564	0.2831	1.1564	1.0754
No log	48.0	384	1.0559	0.2737	1.0559	1.0276
No log	49.0	392	0.9978	0.3048	0.9978	0.9989
No log	50.0	400	1.0286	0.2915	1.0286	1.0142
No log	51.0	408	1.0666	0.2971	1.0666	1.0328
No log	52.0	416	1.0453	0.3117	1.0453	1.0224
No log	53.0	424	0.9973	0.2999	0.9973	0.9987
No log	54.0	432	0.9183	0.3333	0.9183	0.9583
No log	55.0	440	0.9830	0.3081	0.9830	0.9915
No log	56.0	448	0.8649	0.3265	0.8649	0.9300
No log	57.0	456	0.8833	0.3401	0.8833	0.9399
No log	58.0	464	0.8979	0.3252	0.8979	0.9476
No log	59.0	472	0.9125	0.3341	0.9125	0.9553
No log	60.0	480	0.9703	0.3324	0.9703	0.9850
No log	61.0	488	1.1135	0.2901	1.1135	1.0552
No log	62.0	496	1.2968	0.2351	1.2968	1.1388
0.2989	63.0	504	0.8080	0.3533	0.8080	0.8989
0.2989	64.0	512	0.8868	0.3606	0.8868	0.9417
0.2989	65.0	520	0.9297	0.3067	0.9297	0.9642
0.2989	66.0	528	1.0722	0.2375	1.0722	1.0355
0.2989	67.0	536	0.8568	0.3513	0.8568	0.9257
0.2989	68.0	544	0.8640	0.3560	0.8640	0.9295

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 16, 2025
Updated: Mar 16, 2025