training – AI Model by Akaash1 | AlphaNeural AI

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training

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-300m

endpoints_compatible

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training

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.0763
Wer: 0.9551

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: 2
total_train_batch_size: 8
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 25
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.6154	3.3557	500	3.6223	1.0
3.6729	6.7114	1000	3.5869	1.0
3.6718	10.0671	1500	3.5824	1.0
3.7365	13.4228	2000	3.5829	1.0
3.5897	16.7785	2500	3.5750	1.0
3.5689	20.1342	3000	3.2325	1.0
2.4663	23.4899	3500	2.0763	0.9551

Framework versions

Transformers 4.57.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.22.1