predict-perception-bertino-focus-object

gossminn/predict-perception-bertino-focus-object

predict-perception-bertino-focus-object is a text classification model from gossminn. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: distilbert
Access: Public
Created: Jul 14, 2022
Updated: Jul 14, 2022
SHA: 23284365

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Model card

From the Hugging Face model README

predict-perception-bertino-focus-object

This model is a fine-tuned version of indigo-ai/BERTino on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2766
R2: 0.5460

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: 0.0001
train_batch_size: 20
eval_batch_size: 8
seed: 1996
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 47

Training results

Training Loss	Epoch	Step	Validation Loss	R2
0.4798	1.0	14	0.4519	0.2581
0.2481	2.0	28	0.3042	0.5007
0.12	3.0	42	0.3746	0.3851
0.0969	4.0	56	0.3186	0.4770
0.0907	5.0	70	0.3727	0.3882
0.0673	6.0	84	0.2847	0.5327
0.0457	7.0	98	0.3141	0.4844
0.0431	8.0	112	0.3369	0.4470
0.028	9.0	126	0.3039	0.5012
0.0244	10.0	140	0.2964	0.5135
0.0201	11.0	154	0.3072	0.4958
0.0153	12.0	168	0.3049	0.4995
0.0155	13.0	182	0.2924	0.5201
0.015	14.0	196	0.2585	0.5757
0.0181	15.0	210	0.3258	0.4652
0.0136	16.0	224	0.3142	0.4842
0.0105	17.0	238	0.2536	0.5837
0.0104	18.0	252	0.2407	0.6050
0.0107	19.0	266	0.2727	0.5524
0.0084	20.0	280	0.3117	0.4883
0.0102	21.0	294	0.2999	0.5078
0.0074	22.0	308	0.3018	0.5047
0.0068	23.0	322	0.2826	0.5361
0.0054	24.0	336	0.2804	0.5398
0.0044	25.0	350	0.2912	0.5220
0.0048	26.0	364	0.2813	0.5382
0.005	27.0	378	0.2933	0.5186
0.0046	28.0	392	0.2820	0.5371
0.004	29.0	406	0.2717	0.5541
0.0054	30.0	420	0.2717	0.5540
0.0042	31.0	434	0.2699	0.5570
0.0033	32.0	448	0.2630	0.5684
0.0038	33.0	462	0.2578	0.5767
0.0032	34.0	476	0.2687	0.5589
0.004	35.0	490	0.2737	0.5507
0.0031	36.0	504	0.2753	0.5481
0.0037	37.0	518	0.2819	0.5373
0.0034	38.0	532	0.2759	0.5471
0.0034	39.0	546	0.2835	0.5347
0.0029	40.0	560	0.2814	0.5381
0.0033	41.0	574	0.2801	0.5403
0.0025	42.0	588	0.2759	0.5472
0.0029	43.0	602	0.2790	0.5421
0.0028	44.0	616	0.2801	0.5401
0.003	45.0	630	0.2772	0.5451
0.0028	46.0	644	0.2764	0.5463
0.0026	47.0	658	0.2766	0.5460

Framework versions

Transformers 4.16.2
Pytorch 1.10.2+cu113
Datasets 1.18.3
Tokenizers 0.11.0

Task: Text Classification
Library: transformers
Type: distilbert
License: mit
Created: Jul 14, 2022
Updated: Jul 14, 2022