ai-light-dance_drums_ft_pretrain_wav2vec2-base-new_onset-idmt-2_8k

This model is a fine-tuned version of gary109/ai-light-dance_drums_pretrain_wav2vec2-base-new on the GARY109/AI_LIGHT_DANCE - ONSET-IDMT-2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5029
• Wer: 0.3178

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: 0.0003
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 30
• num_epochs: 100.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.0	9	101.8046	0.98
17.4958	2.0	18	82.4920	1.0
16.2087	3.0	27	36.1388	1.0
6.2942	4.0	36	8.3267	1.0
2.0411	5.0	45	6.8215	1.0
1.554	6.0	54	5.3847	1.0
1.6215	7.0	63	4.4645	1.0
1.4962	8.0	72	3.2211	1.0
1.3825	9.0	81	2.5513	1.0
1.3443	10.0	90	2.8582	1.0
1.3443	11.0	99	2.5446	1.0
1.3096	12.0	108	2.0211	0.9956
1.3361	13.0	117	1.8110	0.9944
1.2862	14.0	126	1.7796	0.9933
1.2556	15.0	135	1.7301	0.9922
1.1959	16.0	144	1.4245	0.9989
1.1161	17.0	153	1.1932	0.5678
0.8853	18.0	162	1.2726	0.4922
0.7996	19.0	171	1.0841	0.5511
0.8165	20.0	180	1.4062	0.4411
0.8165	21.0	189	1.4219	0.3367
0.6807	22.0	198	1.2107	0.3344
0.7315	23.0	207	1.1420	0.3189
0.6203	24.0	216	1.0770	0.3778
0.6552	25.0	225	1.1095	0.3789
0.5618	26.0	234	1.0004	0.3478
0.5311	27.0	243	0.8811	0.3311
0.5391	28.0	252	0.8163	0.3678
0.5275	29.0	261	1.0000	0.3311
0.4965	30.0	270	0.7320	0.37
0.4965	31.0	279	0.9643	0.3389
0.4909	32.0	288	0.7663	0.3589
0.5218	33.0	297	0.9004	0.3489
0.4991	34.0	306	0.7342	0.38
0.4883	35.0	315	0.7959	0.3389
0.4902	36.0	324	0.6892	0.3378
0.4447	37.0	333	0.6480	0.3333
0.4458	38.0	342	0.6198	0.3333
0.4607	39.0	351	0.6081	0.3111
0.4352	40.0	360	0.6748	0.3156
0.4352	41.0	369	0.6885	0.3256
0.4286	42.0	378	0.6806	0.3333
0.4314	43.0	387	0.7855	0.3222
0.4476	44.0	396	0.6569	0.3144
0.4815	45.0	405	0.5389	0.3033
0.36	46.0	414	0.5550	0.3011
0.4516	47.0	423	0.5924	0.3144
0.3682	48.0	432	0.7275	0.3056
0.4371	49.0	441	0.7051	0.3089
0.4004	50.0	450	0.5669	0.3078
0.4004	51.0	459	0.5029	0.3178
0.3298	52.0	468	0.6150	0.32
0.4083	53.0	477	0.5882	0.33
0.4022	54.0	486	0.7253	0.3144
0.4465	55.0	495	0.6808	0.3111
0.3955	56.0	504	0.6002	0.3133
0.3877	57.0	513	0.7593	0.3056
0.3486	58.0	522	0.6764	0.3189
0.3782	59.0	531	0.6772	0.3133
0.3599	60.0	540	0.8846	0.3111
0.3599	61.0	549	0.9458	0.3233
0.3424	62.0	558	0.8399	0.3233
0.3652	63.0	567	0.8266	0.3133
0.3327	64.0	576	0.7813	0.3078
0.3603	65.0	585	0.8066	0.3156
0.3401	66.0	594	0.7960	0.3067
0.3797	67.0	603	0.8513	0.2989
0.3353	68.0	612	0.8319	0.2722
0.3909	69.0	621	0.8244	0.2878
0.3263	70.0	630	0.9539	0.3022
0.3263	71.0	639	1.0030	0.2922
0.3102	72.0	648	0.9875	0.3044
0.3577	73.0	657	0.9030	0.2978
0.2953	74.0	666	0.9392	0.2889
0.3644	75.0	675	0.9089	0.2878
0.3231	76.0	684	0.9264	0.2844
0.3078	77.0	693	1.0536	0.2911
0.4503	78.0	702	0.9473	0.2967
0.3492	79.0	711	0.8909	0.3089
0.347	80.0	720	0.8532	0.3067
0.347	81.0	729	0.9553	0.2833
0.2949	82.0	738	1.0111	0.2867
0.3447	83.0	747	0.9160	0.3011
0.2878	84.0	756	0.8401	0.2989
0.3229	85.0	765	0.8815	0.2911
0.276	86.0	774	0.8802	0.2911
0.3469	87.0	783	0.9121	0.29
0.3044	88.0	792	0.8934	0.2933
0.2885	89.0	801	0.8806	0.2967
0.3365	90.0	810	0.9037	0.2844
0.3365	91.0	819	0.9218	0.2867
0.3239	92.0	828	0.9228	0.2844
0.3219	93.0	837	0.9167	0.2844
0.2736	94.0	846	0.9495	0.2878
0.3587	95.0	855	0.9997	0.2844
0.3386	96.0	864	0.9977	0.2856
0.2895	97.0	873	0.9964	0.2889
0.3496	98.0	882	0.9765	0.2889
0.2789	99.0	891	0.9713	0.2878
0.3284	100.0	900	0.9687	0.2889

Framework versions

• Transformers 4.25.0.dev0
• Pytorch 1.8.1+cu111
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2