ast-arabic

fydhfzh/ast-arabic

ast-arabic is a machine learning model from fydhfzh. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as bsd-3-clause.

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

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Hugging Face

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At a glance

License: bsd-3-clause
Model type: audio-spectrogram-transformer
Access: Public
Created: Aug 4, 2024
Updated: Aug 5, 2024
SHA: 0328d8aa

Base models

MIT/ast-finetuned-speech-commands-v2

Model card

From the Hugging Face model README

ast-arabic

This model is a fine-tuned version of MIT/ast-finetuned-speech-commands-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6961
Accuracy: 0.7871
Precision: 0.8186
Recall: 0.7871
F1: 0.7848
Binary: 0.8501

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: 1e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Binary
No log	0.19	50	4.5626	0.0027	0.0001	0.0027	0.0003	0.0860
No log	0.38	100	4.4915	0.0054	0.0037	0.0054	0.0034	0.0954
No log	0.58	150	4.3465	0.0216	0.0105	0.0216	0.0123	0.1488
No log	0.77	200	4.1317	0.0647	0.0355	0.0647	0.0372	0.2356
No log	0.96	250	3.8709	0.1267	0.0963	0.1267	0.0880	0.3245
No log	1.15	300	3.4181	0.2318	0.2405	0.2318	0.1927	0.4442
No log	1.34	350	2.8697	0.3612	0.3714	0.3612	0.3150	0.5426
No log	1.53	400	2.3609	0.4663	0.4425	0.4663	0.4157	0.6248
No log	1.73	450	1.9516	0.5606	0.5573	0.5606	0.5246	0.6903
3.5112	1.92	500	1.6670	0.6092	0.6428	0.6092	0.5849	0.7240
3.5112	2.11	550	1.4376	0.6739	0.6988	0.6739	0.6544	0.7709
3.5112	2.3	600	1.3049	0.6658	0.7019	0.6658	0.6495	0.7636
3.5112	2.49	650	1.1820	0.6846	0.7214	0.6846	0.6731	0.7784
3.5112	2.68	700	1.0847	0.7035	0.7220	0.7035	0.6913	0.7916
3.5112	2.88	750	1.0370	0.7116	0.7415	0.7116	0.7004	0.7973
3.5112	3.07	800	0.9833	0.7062	0.7132	0.7062	0.6903	0.7935
3.5112	3.26	850	0.9453	0.7116	0.7384	0.7116	0.6986	0.7973
3.5112	3.45	900	0.9140	0.7412	0.7724	0.7412	0.7313	0.8181
3.5112	3.64	950	0.8602	0.7493	0.7719	0.7493	0.7403	0.8237
1.0914	3.84	1000	0.8340	0.7520	0.7857	0.7520	0.7469	0.8256
1.0914	4.03	1050	0.8317	0.7628	0.8014	0.7628	0.7602	0.8332
1.0914	4.22	1100	0.7983	0.7628	0.7863	0.7628	0.7584	0.8332
1.0914	4.41	1150	0.8015	0.7601	0.7852	0.7601	0.7529	0.8313
1.0914	4.6	1200	0.7584	0.7709	0.7959	0.7709	0.7685	0.8388
1.0914	4.79	1250	0.7518	0.7763	0.7957	0.7763	0.7699	0.8426
1.0914	4.99	1300	0.7484	0.7520	0.7698	0.7520	0.7449	0.8256
1.0914	5.18	1350	0.7518	0.7466	0.7711	0.7466	0.7397	0.8218
1.0914	5.37	1400	0.7379	0.7682	0.7961	0.7682	0.7654	0.8369
1.0914	5.56	1450	0.7356	0.7601	0.7770	0.7601	0.7533	0.8313
0.6112	5.75	1500	0.7351	0.7763	0.8018	0.7763	0.7720	0.8426
0.6112	5.94	1550	0.7230	0.7655	0.7886	0.7655	0.7631	0.8350
0.6112	6.14	1600	0.7222	0.7709	0.7977	0.7709	0.7656	0.8388
0.6112	6.33	1650	0.7054	0.7790	0.8022	0.7790	0.7744	0.8445
0.6112	6.52	1700	0.7286	0.7736	0.8016	0.7736	0.7693	0.8407
0.6112	6.71	1750	0.6991	0.7925	0.8141	0.7925	0.7907	0.8539
0.6112	6.9	1800	0.7096	0.7655	0.7907	0.7655	0.7633	0.8350
0.6112	7.09	1850	0.7010	0.7844	0.8062	0.7844	0.7821	0.8482
0.6112	7.29	1900	0.7026	0.7574	0.7813	0.7574	0.7514	0.8294
0.6112	7.48	1950	0.6973	0.7817	0.7992	0.7817	0.7785	0.8464
0.4147	7.67	2000	0.7035	0.7736	0.7911	0.7736	0.7707	0.8407
0.4147	7.86	2050	0.6894	0.7844	0.8089	0.7844	0.7827	0.8482
0.4147	8.05	2100	0.7046	0.7763	0.8009	0.7763	0.7731	0.8426
0.4147	8.25	2150	0.6994	0.7817	0.8028	0.7817	0.7786	0.8464
0.4147	8.44	2200	0.6890	0.7763	0.7994	0.7763	0.7723	0.8426
0.4147	8.63	2250	0.6988	0.7763	0.7954	0.7763	0.7722	0.8426
0.4147	8.82	2300	0.7021	0.7763	0.7964	0.7763	0.7731	0.8426
0.4147	9.01	2350	0.6974	0.7817	0.8048	0.7817	0.7784	0.8464
0.4147	9.2	2400	0.6861	0.7817	0.8041	0.7817	0.7807	0.8464
0.4147	9.4	2450	0.6930	0.7763	0.7994	0.7763	0.7734	0.8426
0.3165	9.59	2500	0.6954	0.7763	0.8001	0.7763	0.7741	0.8426
0.3165	9.78	2550	0.6953	0.7817	0.8045	0.7817	0.7794	0.8464
0.3165	9.97	2600	0.6940	0.7817	0.8053	0.7817	0.7794	0.8464

Framework versions

Transformers 4.38.2
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.15.1

Type: audio-spectrogram-transformer
License: bsd-3-clause
Created: Aug 4, 2024
Updated: Aug 5, 2024