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whisper-small_es – AI Model by Jack200133 | AlphaNeural AI
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Jack200133
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whisper-small_es
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper-small_es
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5994
Wer: 55.2083
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: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 125
training_steps: 1000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0065
8.0
250
0.5250
51.9792
0.0009
16.0
500
0.5755
53.0208
0.0006
24.0
750
0.5937
53.125
0.0005
32.0
1000
0.5994
55.2083
Framework versions
Transformers 4.33.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3
