scenario-TCR_data-en-cardiff_eng_only1

haryoaw/scenario-TCR_data-en-cardiff_eng_only1

scenario-TCR_data-en-cardiff_eng_only1 is a text classification model from haryoaw. 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: xlm-roberta
Access: Public
Created: Mar 24, 2024
Updated: Mar 24, 2024
SHA: b91d1dec

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Base models

Model card

From the Hugging Face model README

scenario-TCR_data-en-cardiff_eng_only1

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.8346
Accuracy: 0.5551
F1: 0.5565

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: 32
eval_batch_size: 32
seed: 777
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.03	60	1.1084	0.3638	0.2340
No log	2.07	120	1.0633	0.5181	0.4969
No log	3.1	180	1.0162	0.5106	0.5135
No log	4.14	240	1.0900	0.5573	0.5521
No log	5.17	300	1.2575	0.5644	0.5581
No log	6.21	360	1.4901	0.5489	0.5486
No log	7.24	420	1.7893	0.5560	0.5570
No log	8.28	480	1.8097	0.5767	0.5786
0.6774	9.31	540	1.9894	0.5679	0.5669
0.6774	10.34	600	2.1280	0.5445	0.5443
0.6774	11.38	660	2.4589	0.5653	0.5661
0.6774	12.41	720	2.8356	0.5370	0.5374
0.6774	13.45	780	3.0624	0.5414	0.5370
0.6774	14.48	840	3.1735	0.5410	0.5427
0.6774	15.52	900	3.1008	0.5481	0.5491
0.6774	16.55	960	3.2542	0.5388	0.5411
0.0909	17.59	1020	3.4400	0.5401	0.5415
0.0909	18.62	1080	3.5071	0.5467	0.5491
0.0909	19.66	1140	3.3959	0.5392	0.5375
0.0909	20.69	1200	3.5250	0.5507	0.5531
0.0909	21.72	1260	3.5264	0.5569	0.5588
0.0909	22.76	1320	3.6723	0.5516	0.5529
0.0909	23.79	1380	3.6306	0.5595	0.5614
0.0909	24.83	1440	3.7656	0.5476	0.5480
0.0131	25.86	1500	3.7895	0.5578	0.5594
0.0131	26.9	1560	3.7447	0.5591	0.5601
0.0131	27.93	1620	3.8071	0.5551	0.5572
0.0131	28.97	1680	3.8322	0.5556	0.5572
0.0131	30.0	1740	3.8346	0.5551	0.5565

Framework versions

Transformers 4.33.3
Pytorch 2.1.1+cu121
Datasets 2.14.5
Tokenizers 0.13.3

Task: Text Classification
Library: transformers
Type: xlm-roberta
License: mit
Created: Mar 24, 2024
Updated: Mar 24, 2024