language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Tunisian Checkpoint1.5
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: custom_tunisian_dataset
type: dataset
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 51.80948419301165
- name: Cer
type: cer
value: 25.522807875749052
Model Card for Model ID
Finetuning Whisper on Tunisian custom dataset
Model Details
Model Description
This model is a fine-tuned version of openai/whisper-small on the tunisian_custom dataset (2h and 30mn). It achieves the following results on the evaluation set:
Train Loss: 0.0029
Evaluation Loss: 1.1970311403274536
Wer: 51.80948419301165
Cer: 25.522807875749052
Developed by: [Ameni Khabthani]
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Model type: [ASR system]
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Finetuned from model [optional]: [whisper small]
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Training Details
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Training Procedure
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Training Hyperparameters
per_device_train_batch_size=8
gradient_accumulation_steps=8
learning_rate= 5e-5
warmup_steps=100
max_steps=3000
gradient_checkpointing=True
fp16=True
save_steps=500
eval_steps=500
per_device_eval_batch_size=8
predict_with_generate=True
generation_max_length=225
logging_steps=50,
optim="adamw_bnb_8bit"
weight_decay=0.01
dropout=0.1
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Evaluation
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Summary
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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