userutterance_classification_ver1

dhruvil237/userutterance_classification_ver1

userutterance_classification_ver1 is a text classification model from dhruvil237. 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: deberta-v2
Access: Public
Created: Mar 1, 2023
Updated: May 18, 2023
SHA: f4b6e6f9

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Datasets

clinc_oos

Model card

From the Hugging Face model README

userutterance_classification_ver1

This model is a fine-tuned version of microsoft/deberta-v3-base on the clinc_oos dataset. It achieves the following results on the evaluation set:

Loss: 0.2898
Accuracy: 0.9539

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: 4e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 130
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
4.8334	0.15	200	4.7254	0.0748
3.4798	0.3	400	3.4244	0.2971
2.319	0.45	600	2.4423	0.5184
1.5683	0.6	800	1.7401	0.6310
0.9625	0.75	1000	1.2750	0.7265
0.6922	0.9	1200	0.9717	0.7761
0.5019	1.05	1400	0.8036	0.8284
0.3538	1.2	1600	0.6690	0.8471
0.2413	1.35	1800	0.5585	0.8713
0.2623	1.5	2000	0.4840	0.8874
0.2103	1.66	2200	0.4261	0.9126
0.1456	1.81	2400	0.3872	0.9152
0.1276	1.96	2600	0.3329	0.9290
0.09	2.11	2800	0.2925	0.9432
0.0534	2.26	3000	0.2996	0.9361
0.0588	2.41	3200	0.2951	0.9403
0.044	2.56	3400	0.3324	0.9403
0.0535	2.71	3600	0.3155	0.9432
0.0537	2.86	3800	0.3206	0.9419
0.1325	3.01	4000	0.2945	0.9465
0.0611	3.16	4200	0.2903	0.9442
0.0077	3.31	4400	0.3052	0.9477
0.0187	3.46	4600	0.2774	0.95
0.0125	3.61	4800	0.2851	0.9513
0.0157	3.76	5000	0.2883	0.9523
0.0414	3.91	5200	0.3163	0.9497
0.0025	4.06	5400	0.2998	0.9494
0.0019	4.21	5600	0.2925	0.9513
0.0013	4.36	5800	0.2872	0.9526
0.0014	4.51	6000	0.2906	0.9532
0.0015	4.67	6200	0.2862	0.9529
0.0281	4.82	6400	0.2863	0.9535
0.0287	4.97	6600	0.2898	0.9539

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

Task: Text Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Mar 1, 2023
Updated: May 18, 2023