library_name: transformers | |
license: apache-2.0 | |
base_model: openai/whisper-small | |
tags: | |
- generated_from_trainer | |
model-index: | |
- name: whisper-small-sc | |
results: [] | |
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should probably proofread and complete it, then remove this comment. --> | |
# whisper-small-sc | |
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset. | |
It achieves the following results on the evaluation set: | |
- eval_loss: 0.2616 | |
- eval_wer_ortho: 11.1994 | |
- eval_wer: 10.7122 | |
- eval_runtime: 1028.1037 | |
- eval_samples_per_second: 4.343 | |
- eval_steps_per_second: 0.136 | |
- epoch: 4.6012 | |
- step: 750 | |
## 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: 5e-06 | |
- train_batch_size: 64 | |
- eval_batch_size: 32 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- lr_scheduler_warmup_steps: 250 | |
- training_steps: 2500 | |
- mixed_precision_training: Native AMP | |
### Framework versions | |
- Transformers 4.44.2 | |
- Pytorch 2.4.0 | |
- Datasets 2.21.0 | |
- Tokenizers 0.19.1 | |