hbertv1-massive-logit_KD-tiny_ffn_1

gokuls/hbertv1-massive-logit_KD-tiny_ffn_1

hbertv1-massive-logit_KD-tiny_ffn_1 is a text classification model from gokuls. 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. --

Downloads · 30 days

16% of all-time downloads

All-time downloads

Public

Parameters

4.2M

834 MB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors17 MB · 94%

At a glance

Task: Text Classification
Library: transformers
Model type: hybridbert
Access: Public
Created: Nov 26, 2023
Updated: Nov 26, 2023
SHA: 9fb16389

Try a prompt

Base models

gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_1

Datasets

massive

Model card

From the Hugging Face model README

hbertv1-massive-logit_KD-tiny_ffn_1

This model is a fine-tuned version of gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_1 on the massive dataset. It achieves the following results on the evaluation set:

Loss: 0.6331
Accuracy: 0.8342

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: 64
eval_batch_size: 64
seed: 33
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
4.296	1.0	180	3.7345	0.2081
3.5386	2.0	360	3.0526	0.2730
2.9946	3.0	540	2.6051	0.3360
2.6126	4.0	720	2.2810	0.4215
2.3148	5.0	900	2.0377	0.4683
2.0838	6.0	1080	1.8401	0.5371
1.9016	7.0	1260	1.6686	0.6080
1.7431	8.0	1440	1.5358	0.6439
1.613	9.0	1620	1.4238	0.6886
1.4952	10.0	1800	1.3339	0.7127
1.4	11.0	1980	1.2511	0.7162
1.3069	12.0	2160	1.1877	0.7285
1.2288	13.0	2340	1.1277	0.7329
1.1684	14.0	2520	1.0877	0.7418
1.0971	15.0	2700	1.0285	0.7570
1.0424	16.0	2880	0.9811	0.7619
0.9865	17.0	3060	0.9552	0.7629
0.943	18.0	3240	0.9216	0.7742
0.9047	19.0	3420	0.8812	0.7762
0.857	20.0	3600	0.8619	0.7821
0.8274	21.0	3780	0.8326	0.7914
0.7955	22.0	3960	0.8086	0.7919
0.7618	23.0	4140	0.7861	0.7973
0.7356	24.0	4320	0.7750	0.7993
0.7109	25.0	4500	0.7580	0.8028
0.6872	26.0	4680	0.7430	0.8077
0.6683	27.0	4860	0.7417	0.8101
0.6503	28.0	5040	0.7132	0.8155
0.6279	29.0	5220	0.7100	0.8106
0.6168	30.0	5400	0.6991	0.8165
0.5981	31.0	5580	0.6935	0.8185
0.5816	32.0	5760	0.6843	0.8200
0.5746	33.0	5940	0.6795	0.8155
0.5602	34.0	6120	0.6775	0.8210
0.5525	35.0	6300	0.6683	0.8244
0.5403	36.0	6480	0.6641	0.8219
0.5289	37.0	6660	0.6598	0.8278
0.5245	38.0	6840	0.6546	0.8278
0.518	39.0	7020	0.6523	0.8259
0.5105	40.0	7200	0.6488	0.8283
0.4988	41.0	7380	0.6463	0.8278
0.4971	42.0	7560	0.6414	0.8308
0.491	43.0	7740	0.6376	0.8318
0.4901	44.0	7920	0.6395	0.8298
0.4846	45.0	8100	0.6348	0.8298
0.4805	46.0	8280	0.6357	0.8313
0.481	47.0	8460	0.6320	0.8313
0.4767	48.0	8640	0.6331	0.8342
0.474	49.0	8820	0.6319	0.8328
0.4765	50.0	9000	0.6318	0.8308

Framework versions

Transformers 4.35.2
Pytorch 1.14.0a0+410ce96
Datasets 2.15.0
Tokenizers 0.15.0

Task: Text Classification
Library: transformers
Type: hybridbert
Created: Nov 26, 2023
Updated: Nov 26, 2023