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fydhfzh/
ast-arabic

Name: ast-arabic
Availability: InStock

tensorboard

safetensors

audio-spectrogram-transformer

generated_from_trainer

MIT/ast-finetuned-speech-commands-v2

finetune

bsd-3-clause

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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

fydhfzh/ast-arabic

ast-arabic

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fydhfzh/
ast-arabic