my_awesome_asr_mind_model_m – AI Model by amira-morsli | AlphaNeural AI

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my_awesome_asr_mind_model_m

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my_awesome_asr_mind_model_m

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 6.1679
Wer: 1.1256

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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: 2000
training_steps: 26000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4698	200.0	1000	3.4251	1.0
2.8391	400.0	2000	2.9903	1.0
2.5123	600.0	3000	2.9246	1.0
2.0536	800.0	4000	2.9389	0.9955
1.4949	1000.0	5000	3.1124	0.9776
1.0579	1200.0	6000	3.6074	1.0179
0.7578	1400.0	7000	3.8384	1.0314
0.5393	1600.0	8000	4.2573	1.0448
0.3935	1800.0	9000	4.4847	1.0448
0.3049	2000.0	10000	5.0460	1.0852
0.2482	2200.0	11000	4.9277	1.0807
0.2027	2400.0	12000	5.3025	1.1121
0.1653	2600.0	13000	5.5421	1.1031
0.1496	2800.0	14000	5.6074	1.0762
0.1221	3000.0	15000	5.4166	1.1031
0.1121	3200.0	16000	5.8223	1.1300
0.097	3400.0	17000	5.8823	1.1525
0.0908	3600.0	18000	5.8555	1.1211
0.0853	3800.0	19000	6.0204	1.1256
0.0743	4000.0	20000	5.8911	1.1076
0.0735	4200.0	21000	6.1458	1.1076
0.0701	4400.0	22000	6.1057	1.1166
0.0657	4600.0	23000	6.0016	1.1031
0.0659	4800.0	24000	6.0810	1.1256
0.0621	5000.0	25000	6.1174	1.1256
0.0602	5200.0	26000	6.1679	1.1256

Framework versions

Transformers 4.28.0
Pytorch 2.0.1
Datasets 2.14.5
Tokenizers 0.13.3