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# Whisper finetuned for ceb

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Fleurs Ceb subset, LSK nonsynthetic, Onetalk Q&A, and Ceb sentences dataset dataset.

## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 100
- training_steps: 20000

### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1

{"language": ["ceb"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["nlewins/ceb-sentences-with-audio", "nlewins/standard_dataset_nonsynthetic"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper finetuned for ceb", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer ceb dataset:nlewins/ceb-sentences-with-audio dataset:nlewins/standard_dataset_nonsynthetic base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us