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whisper_large_v2_fixed_timestamps – AI Model by PThi35 | AlphaNeural AI
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whisper_large_v2_fixed_timestamps
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safetensors
whisper
generated_from_trainer
openai/whisper-large-v2
finetune
apache-2.0
us
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whisper_large_v2_fixed_timestamps
This model is a fine-tuned version of
openai/whisper-large-v2
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6408
Cer: 14.2277
Wer: 24.0848
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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
Wer
0.8984
1.0
6265
0.6727
15.8499
27.0820
0.6156
2.0
12530
0.6507
15.4948
26.1944
0.5175
3.0
18795
0.6408
14.2277
24.0848
Framework versions
Transformers 4.41.2
Pytorch 2.1.2+cu118
Datasets 2.19.0
Tokenizers 0.19.1
