final_V1-roberta-text-classification-model

AmirlyPhd/final_V1-roberta-text-classification-model

final_V1-roberta-text-classification-model is a text classification model from AmirlyPhd. 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: roberta
Access: Public
Created: Apr 29, 2024
Updated: Apr 29, 2024
SHA: 846aa932

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Base models

Model card

From the Hugging Face model README

final_V1-roberta-text-classification-model

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2641
Accuracy: 0.9502
F1: 0.8186
Precision: 0.8164
Recall: 0.8225

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: 5e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.6615	0.11	50	1.5503	0.3199	0.1016	0.2599	0.1518
0.6244	0.22	100	0.7198	0.7692	0.4656	0.4593	0.4818
0.3344	0.33	150	0.4852	0.8893	0.6484	0.6264	0.6733
0.2596	0.44	200	0.5277	0.8805	0.6398	0.6124	0.6748
0.2173	0.55	250	0.4417	0.8849	0.6577	0.6421	0.6750
0.2393	0.66	300	0.5221	0.8707	0.6511	0.6361	0.6684
0.2229	0.76	350	0.4997	0.8928	0.6602	0.6410	0.6814
0.1482	0.87	400	0.5111	0.8983	0.6409	0.6131	0.6810
0.1831	0.98	450	0.4251	0.8827	0.6827	0.7149	0.6957
0.1882	1.09	500	0.4130	0.9043	0.6805	0.7998	0.6878
0.1182	1.2	550	0.4513	0.9076	0.6973	0.7703	0.7004
0.101	1.31	600	0.3402	0.9221	0.7040	0.8097	0.7036
0.0749	1.42	650	0.1566	0.9658	0.8229	0.8350	0.8122
0.1294	1.53	700	0.1586	0.9675	0.8336	0.8327	0.8346
0.046	1.64	750	0.2010	0.9604	0.8264	0.8211	0.8334
0.0833	1.75	800	0.1707	0.9647	0.8285	0.8244	0.8330
0.0759	1.86	850	0.1625	0.9664	0.8278	0.8285	0.8271
0.0459	1.97	900	0.1831	0.9620	0.8258	0.8200	0.8328
0.0726	2.07	950	0.1753	0.9625	0.8279	0.8287	0.8276
0.0369	2.18	1000	0.1871	0.9650	0.8300	0.8252	0.8362
0.0456	2.29	1050	0.1524	0.9683	0.8320	0.8278	0.8367
0.0371	2.4	1100	0.1857	0.9631	0.8280	0.8219	0.8353
0.0106	2.51	1150	0.1850	0.9661	0.8318	0.8274	0.8370
0.0173	2.62	1200	0.2055	0.9647	0.8310	0.8259	0.8374
0.036	2.73	1250	0.1699	0.9694	0.8311	0.8267	0.8358
0.0176	2.84	1300	0.1780	0.9691	0.8325	0.8274	0.8382
0.0444	2.95	1350	0.1918	0.9672	0.8319	0.8275	0.8371

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2

Task: Text Classification
Library: transformers
Type: roberta
License: mit
Created: Apr 29, 2024
Updated: Apr 29, 2024