benek3
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whisper-small-pl

Automatic Speech Recognition

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Whisper Small2.0 PL

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.4425
Wer: 25.4141

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0076	4.8356	5000	0.4425	25.4141

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

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Safetensors

Model size

242M params

Tensor type

F32

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Model tree for benek3/whisper-small-pl

Base model

openai/whisper-small

Finetuned

(2496)

this model

Dataset used to train benek3/whisper-small-pl

Evaluation results

Wer on Common Voice 11.0
test set self-reported

25.414

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