wav2vec2-speech-project-subsetData – AI Model by daniyalahmad | AlphaNeural AI

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daniyalahmad/
wav2vec2-speech-project-subsetData

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wav2vec2-speech-project-subsetData

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: 0.1157
Wer: 0.2453

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
14.9506	1.67	50	16.5714	1.0
7.9883	3.33	100	4.1299	1.0
3.4027	5.0	150	3.2576	1.0
3.1425	6.67	200	3.0644	1.0
3.0198	8.33	250	2.9955	1.0
2.974	10.0	300	2.9685	1.0
2.9492	11.67	350	2.9520	1.0
2.9225	13.33	400	3.0013	1.0
2.8383	15.0	450	2.7433	1.0
2.5389	16.67	500	2.1815	1.0
1.8402	18.33	550	1.2757	0.9653
0.926	20.0	600	0.4806	0.4453
0.4593	21.67	650	0.3497	0.376
0.3047	23.33	700	0.1765	0.2507
0.2407	25.0	750	0.1152	0.216
0.1867	26.67	800	0.2214	0.2987
0.1637	28.33	850	0.1050	0.2453
0.1599	30.0	900	0.1157	0.2453

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 1.18.3
Tokenizers 0.13.3