rubert-base-cased_best_finetuned_emotion_experiment_augmented_anger_fear

mmillet/rubert-base-cased_best_finetuned_emotion_experiment_augmented_anger_fear

rubert-base-cased_best_finetuned_emotion_experiment_augmented_anger_fear is a text classification model from mmillet. 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: bert
Access: Public
Created: Jun 8, 2022
Updated: Jun 8, 2022
SHA: 0c29a323

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Model card

From the Hugging Face model README

rubert-base-cased_best_finetuned_emotion_experiment_augmented_anger_fear

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

Loss: 0.4568
Accuracy: 0.8779
F1: 0.8777
Precision: 0.8780
Recall: 0.8779

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: Adam with betas=(0.9,0.999) and epsilon=0.0001
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.2647	1.0	69	1.0075	0.6013	0.5671	0.6594	0.6013
0.9091	2.0	138	0.7853	0.7171	0.7138	0.7169	0.7171
0.7305	3.0	207	0.6264	0.7829	0.7811	0.7835	0.7829
0.5446	4.0	276	0.4571	0.8466	0.8465	0.8470	0.8466
0.4039	5.0	345	0.4035	0.8612	0.8606	0.8612	0.8612
0.3144	6.0	414	0.3800	0.8653	0.8653	0.8665	0.8653
0.2711	7.0	483	0.3731	0.8674	0.8673	0.8677	0.8674
0.2289	8.0	552	0.4041	0.8737	0.8728	0.8746	0.8737
0.1944	9.0	621	0.4002	0.8789	0.8785	0.8793	0.8789
0.171	10.0	690	0.3939	0.8831	0.8827	0.8839	0.8831
0.138	11.0	759	0.4106	0.8758	0.8754	0.8761	0.8758
0.1141	12.0	828	0.4200	0.8810	0.8803	0.8804	0.8810
0.1141	13.0	897	0.4426	0.8758	0.8756	0.8763	0.8758
0.0961	14.0	966	0.4494	0.8758	0.8754	0.8761	0.8758
0.0812	15.0	1035	0.4568	0.8779	0.8777	0.8780	0.8779

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
Created: Jun 8, 2022
Updated: Jun 8, 2022