bart-large

xshubhamx/bart-large

bart-large is a text classification model from xshubhamx. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bart
Access: Public
Created: Apr 20, 2024
Updated: Apr 21, 2024
SHA: dbee9b14

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Base models

facebook/bart-large

Model card

From the Hugging Face model README

bart-large

This model is a fine-tuned version of facebook/bart-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.0027
Accuracy: 0.7916
Precision: 0.7858
Recall: 0.7916
Precision Macro: 0.7201
Recall Macro: 0.7056
Macro Fpr: 0.0201
Weighted Fpr: 0.0195
Weighted Specificity: 0.9714
Macro Specificity: 0.9836
Weighted Sensitivity: 0.7823
Macro Sensitivity: 0.7056
F1 Micro: 0.7823
F1 Macro: 0.7080
F1 Weighted: 0.7801

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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	Precision Macro	Recall Macro	Macro Fpr	Weighted Fpr	Weighted Specificity	Macro Specificity	Weighted Sensitivity	Macro Sensitivity	F1 Micro	F1 Macro	F1 Weighted
1.1685	1.0	2569	1.2587	0.6847	0.6360	0.6847	0.4176	0.4720	0.0331	0.0318	0.9550	0.9760	0.6847	0.4720	0.6847	0.4296	0.6471
1.1965	2.0	5138	1.1623	0.6638	0.6943	0.6638	0.4564	0.4261	0.0342	0.0349	0.9654	0.9753	0.6638	0.4261	0.6638	0.3955	0.6468
1.189	3.0	7707	1.3574	0.7235	0.7220	0.7235	0.5413	0.5528	0.0271	0.0266	0.9628	0.9791	0.7235	0.5528	0.7235	0.5196	0.7031
1.0127	4.0	10276	1.4685	0.7668	0.7584	0.7668	0.6671	0.6202	0.0224	0.0213	0.9653	0.9821	0.7668	0.6202	0.7668	0.6233	0.7569
1.0205	5.0	12845	1.4232	0.7668	0.7711	0.7668	0.6765	0.6872	0.0215	0.0213	0.9737	0.9827	0.7668	0.6872	0.7668	0.6732	0.7643
0.7927	6.0	15414	1.5678	0.7428	0.7451	0.7428	0.6489	0.6333	0.0248	0.0241	0.9690	0.9808	0.7428	0.6333	0.7428	0.6108	0.7292
0.7701	7.0	17983	1.7337	0.7467	0.7600	0.7467	0.6863	0.6536	0.0240	0.0237	0.9680	0.9810	0.7467	0.6536	0.7467	0.6584	0.7399
0.584	8.0	20552	1.6188	0.7692	0.7766	0.7692	0.6979	0.7065	0.0214	0.0210	0.9706	0.9827	0.7692	0.7065	0.7692	0.6980	0.7683
0.5659	9.0	23121	1.6983	0.7599	0.7665	0.7599	0.7000	0.6804	0.0227	0.0221	0.9695	0.9820	0.7599	0.6804	0.7599	0.6728	0.7542
0.7021	10.0	25690	1.6445	0.7699	0.7656	0.7699	0.7144	0.6857	0.0223	0.0209	0.9608	0.9821	0.7699	0.6857	0.7699	0.6954	0.7634
0.6216	11.0	28259	1.6562	0.7676	0.7634	0.7676	0.6856	0.6776	0.0223	0.0212	0.9640	0.9821	0.7676	0.6776	0.7676	0.6786	0.7624
0.6408	12.0	30828	1.6682	0.7668	0.7629	0.7668	0.6706	0.6719	0.0223	0.0213	0.9666	0.9822	0.7668	0.6719	0.7668	0.6666	0.7608
0.523	13.0	33397	1.7727	0.7653	0.7674	0.7653	0.8238	0.6934	0.0226	0.0214	0.9659	0.9821	0.7653	0.6934	0.7653	0.7066	0.7534
0.3688	14.0	35966	1.8404	0.7792	0.7788	0.7792	0.7229	0.6921	0.0209	0.0198	0.9675	0.9831	0.7792	0.6921	0.7792	0.6960	0.7731
0.2394	15.0	38535	1.7885	0.7816	0.7809	0.7816	0.7441	0.7115	0.0210	0.0196	0.9628	0.9830	0.7816	0.7115	0.7816	0.7230	0.7765
0.2734	16.0	41104	1.8944	0.7777	0.7870	0.7777	0.7539	0.7265	0.0203	0.0200	0.9724	0.9833	0.7777	0.7265	0.7777	0.7295	0.7777
0.4319	17.0	43673	1.7744	0.7885	0.7847	0.7885	0.7247	0.7320	0.0195	0.0188	0.9718	0.9840	0.7885	0.7320	0.7885	0.7269	0.7855
0.2347	18.0	46242	2.0036	0.7413	0.7352	0.7413	0.6934	0.6799	0.0255	0.0243	0.9597	0.9801	0.7413	0.6799	0.7413	0.6825	0.7354
0.1882	19.0	48811	1.9298	0.7816	0.7804	0.7816	0.7243	0.7262	0.0202	0.0196	0.9708	0.9835	0.7816	0.7262	0.7816	0.7225	0.7792
0.1799	20.0	51380	1.9688	0.7792	0.7892	0.7792	0.7312	0.7343	0.0205	0.0198	0.9714	0.9834	0.7792	0.7343	0.7792	0.7242	0.7779
0.1366	21.0	53949	1.9910	0.7847	0.7846	0.7847	0.7148	0.7455	0.0198	0.0192	0.9730	0.9838	0.7847	0.7455	0.7847	0.7265	0.7833
0.1793	22.0	56518	2.2548	0.7630	0.7648	0.7630	0.7150	0.7273	0.0230	0.0217	0.9633	0.9818	0.7630	0.7273	0.7630	0.7150	0.7582
0.1749	23.0	59087	2.1109	0.7816	0.7768	0.7816	0.7466	0.7230	0.0205	0.0196	0.9690	0.9834	0.7816	0.7230	0.7816	0.7289	0.7774
0.1154	24.0	61656	2.0637	0.7878	0.7837	0.7878	0.7590	0.7269	0.0196	0.0189	0.9718	0.9840	0.7878	0.7269	0.7878	0.7331	0.7828
0.1447	25.0	64225	2.0027	0.7916	0.7858	0.7916	0.7750	0.7299	0.0194	0.0185	0.9697	0.9841	0.7916	0.7299	0.7916	0.7408	0.7861
0.0806	26.0	66794	2.0777	0.7885	0.7831	0.7885	0.7162	0.7134	0.0196	0.0188	0.9715	0.9840	0.7885	0.7134	0.7885	0.7118	0.7840
0.0407	27.0	69363	2.1754	0.7885	0.7863	0.7885	0.7192	0.7080	0.0194	0.0188	0.9725	0.9841	0.7885	0.7080	0.7885	0.7105	0.7866
0.0701	28.0	71932	2.1578	0.7823	0.7817	0.7823	0.7130	0.7097	0.0201	0.0195	0.9714	0.9836	0.7823	0.7097	0.7823	0.7066	0.7810
0.1034	29.0	74501	2.2132	0.7800	0.7789	0.7800	0.7163	0.7044	0.0203	0.0197	0.9713	0.9834	0.7800	0.7044	0.7800	0.7064	0.7785
0.0388	30.0	77070	2.1833	0.7823	0.7806	0.7823	0.7201	0.7056	0.0201	0.0195	0.9714	0.9836	0.7823	0.7056	0.7823	0.7080	0.7801

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.19.0
Tokenizers 0.15.1

Task: Text Classification
Library: transformers
Type: bart
License: apache-2.0
Created: Apr 20, 2024
Updated: Apr 21, 2024