asr-nepali – AI Model by Ashwini1412 | AlphaNeural AI

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Ashwini1412/
asr-nepali

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-large-xlsr-53

endpoints_compatible

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asr-nepali

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

Loss: nan
Wer: 1.0
Cer: 0.9965
Accuracy: 0.0035

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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: 180
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer	Accuracy
451.545	1.46	100	43.3285	1.0	0.9684	0.0316
194.4567	2.92	200	nan	1.0	0.9965	0.0035
0.0	4.38	300	nan	1.0	0.9965	0.0035
0.0	5.84	400	nan	1.0	0.9965	0.0035
0.0	7.3	500	nan	1.0	0.9965	0.0035
0.0	8.76	600	nan	1.0	0.9965	0.0035
0.0	10.22	700	nan	1.0	0.9965	0.0035
0.0	11.68	800	nan	1.0	0.9965	0.0035
0.0	13.14	900	nan	1.0	0.9965	0.0035
0.0	14.6	1000	nan	1.0	0.9965	0.0035
0.0	16.06	1100	nan	1.0	0.9965	0.0035
0.0	17.52	1200	nan	1.0	0.9965	0.0035
0.0	18.98	1300	nan	1.0	0.9965	0.0035
0.0	20.44	1400	nan	1.0	0.9965	0.0035
0.0	21.9	1500	nan	1.0	0.9965	0.0035
0.0	23.36	1600	nan	1.0	0.9965	0.0035
0.0	24.82	1700	nan	1.0	0.9965	0.0035
0.0	26.28	1800	nan	1.0	0.9965	0.0035
0.0	27.74	1900	nan	1.0	0.9965	0.0035
0.0	29.2	2000	nan	1.0	0.9965	0.0035

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0