textattack-roberta-base-MNLI-e-snli-classification-nli-base

k4black/textattack-roberta-base-MNLI-e-snli-classification-nli-base

textattack-roberta-base-MNLI-e-snli-classification-nli-base is a text classification model from k4black. Use it when you need a label for a piece of text. It is set up for transformers.

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

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At a glance

Task: Text Classification
Library: transformers
Model type: roberta
Access: Public
Created: Mar 21, 2023
Updated: Mar 21, 2023
SHA: 5040fba3

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Datasets

esnli

Model card

From the Hugging Face model README

textattack-roberta-base-MNLI-e-snli-classification-nli-base

This model is a fine-tuned version of textattack/roberta-base-MNLI on the esnli dataset. It achieves the following results on the evaluation set:

Loss: 0.2488
F1: 0.9106
Accuracy: 0.9111

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
1.5376	0.05	400	0.4010	0.8556	0.8556
0.4352	0.09	800	0.3349	0.8795	0.8800
0.4	0.14	1200	0.3180	0.8851	0.8854
0.3801	0.19	1600	0.2975	0.8918	0.8921
0.3599	0.23	2000	0.2949	0.8951	0.8955
0.3612	0.28	2400	0.2802	0.8987	0.8987
0.3519	0.33	2800	0.2763	0.8977	0.8980
0.349	0.37	3200	0.2766	0.9020	0.9023
0.3432	0.42	3600	0.2748	0.9000	0.9001
0.3435	0.47	4000	0.2702	0.9051	0.9051
0.3352	0.51	4400	0.2728	0.9034	0.9039
0.3277	0.56	4800	0.2634	0.9039	0.9043
0.3307	0.61	5200	0.2623	0.9050	0.9057
0.3247	0.65	5600	0.2685	0.9059	0.9063
0.3175	0.7	6000	0.2589	0.9081	0.9084
0.3144	0.75	6400	0.2586	0.9088	0.9093
0.3102	0.79	6800	0.2547	0.9088	0.9090
0.3223	0.84	7200	0.2526	0.9093	0.9096
0.3166	0.89	7600	0.2490	0.9115	0.9118
0.3124	0.93	8000	0.2503	0.9106	0.9107
0.3053	0.98	8400	0.2452	0.9099	0.9101
0.2908	1.03	8800	0.2575	0.9113	0.9119
0.2853	1.07	9200	0.2464	0.9114	0.9118
0.2796	1.12	9600	0.2488	0.9106	0.9111

Framework versions

Transformers 4.27.1
Pytorch 1.12.1+cu113
Datasets 2.10.1
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: roberta
Created: Mar 21, 2023
Updated: Mar 21, 2023