You can deploy this model and start earning money today!

naleraphael/
rasr_sample

Name: rasr_sample
Availability: InStock

transformers

pytorch

wav2vec2

automatic-speech-recognition

mozilla-foundation/common_voice_7_0

generated_from_trainer

common_voice

apache-2.0

endpoints_compatible

Views

No views yet

rasr_sample

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - SV-SE dataset. It achieves the following results on the evaluation set:

Loss: 0.3147
Wer: 0.2676

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: 7.5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2000
num_epochs: 50.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.3332	1.45	500	3.3031	1.0
2.9272	2.91	1000	2.9353	0.9970
2.0736	4.36	1500	1.1565	0.8714
1.7339	5.81	2000	0.7156	0.6688
1.5989	7.27	2500	0.5791	0.5519
1.4916	8.72	3000	0.5038	0.5169
1.4562	10.17	3500	0.4861	0.4805
1.3893	11.63	4000	0.4584	0.4761
1.3797	13.08	4500	0.4298	0.4686
1.3508	14.53	5000	0.4138	0.3744
1.3165	15.99	5500	0.4015	0.3578
1.281	17.44	6000	0.3883	0.3472
1.2682	18.89	6500	0.3904	0.3434
1.2477	20.35	7000	0.3726	0.3321
1.2364	21.8	7500	0.3685	0.3281
1.2041	23.26	8000	0.3597	0.3194
1.1901	24.71	8500	0.3542	0.3203
1.1903	26.16	9000	0.3500	0.3138
1.1677	27.61	9500	0.3458	0.3067
1.1718	29.07	10000	0.3595	0.3112
1.1562	30.52	10500	0.3433	0.3022
1.1392	31.97	11000	0.3440	0.2936
1.1258	33.43	11500	0.3396	0.2950
1.1067	34.88	12000	0.3379	0.2939
1.0953	36.34	12500	0.3370	0.2868
1.0835	37.79	13000	0.3317	0.2860
1.0772	39.24	13500	0.3302	0.2854
1.0853	40.7	14000	0.3265	0.2783
1.0689	42.15	14500	0.3306	0.2770
1.0394	43.6	15000	0.3233	0.2757
1.0581	45.06	15500	0.3199	0.2713
1.0362	46.51	16000	0.3154	0.2683
1.0406	47.96	16500	0.3176	0.2688
1.0082	49.42	17000	0.3149	0.2679

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.2+cu102
Datasets 1.18.2.dev0
Tokenizers 0.11.0

naleraphael/rasr_sample

rasr_sample

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

naleraphael/
rasr_sample