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daniel_whisper_finetune_medium_v2 – AI Model by danielrosehill | AlphaNeural AI
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daniel_whisper_finetune_medium_v2
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transformers
pytorch
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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daniel_whisper_finetune_medium_v2
This model is a fine-tuned version of
openai/whisper-medium
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1799
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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50
training_steps: 250
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
1.1622
1.3158
50
0.4810
0.06
2.6316
100
0.1686
0.0207
3.9474
150
0.1639
0.0078
5.2632
200
0.1709
0.0036
6.5789
250
0.1799
Framework versions
Transformers 4.57.1
Pytorch 2.9.1+cu128
Datasets 4.4.1
Tokenizers 0.22.1
