ap-rjt11wGQrIfbImBuMcanEA – AI Model by mdsingh2024 | AlphaNeural AI

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mdsingh2024/
ap-rjt11wGQrIfbImBuMcanEA

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automatic-speech-recognition

generated_from_trainer

openai/whisper-large-v3

endpoints_compatible

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ap-rjt11wGQrIfbImBuMcanEA

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4495
Model Preparation Time: 0.0152
Wer: 0.1392

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Use OptimizerNames.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: 400
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Wer
0.2309	1.0	34	0.2776	0.0152	0.1225
0.1721	2.0	68	0.3076	0.0152	0.1177
0.0577	3.0	102	0.3592	0.0152	0.1180
0.0859	4.0	136	0.4658	0.0152	0.1467
0.0962	4.8722	165	0.4495	0.0152	0.1392

Framework versions

Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0