|
|
---
|
|
|
library_name: transformers
|
|
|
license: apache-2.0
|
|
|
base_model: openai/whisper-base
|
|
|
tags:
|
|
|
- generated_from_trainer
|
|
|
model-index:
|
|
|
- name: whisper-base
|
|
|
results: []
|
|
|
---
|
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
should probably proofread and complete it, then remove this comment. -->
|
|
|
|
|
|
# whisper-base
|
|
|
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
|
|
|
It achieves the following results on the evaluation set:
|
|
|
- eval_loss: 1.0027
|
|
|
- eval_wer: 0.3287
|
|
|
- eval_runtime: 19.3097
|
|
|
- eval_samples_per_second: 5.852
|
|
|
- eval_steps_per_second: 0.207
|
|
|
- epoch: 47.5333
|
|
|
- step: 380
|
|
|
|
|
|
## 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: 32
|
|
|
- eval_batch_size: 32
|
|
|
- seed: 42
|
|
|
- gradient_accumulation_steps: 2
|
|
|
- total_train_batch_size: 64
|
|
|
- optimizer: Use adafactor and the args are:
|
|
|
No additional optimizer arguments
|
|
|
- lr_scheduler_type: linear
|
|
|
- lr_scheduler_warmup_steps: 100
|
|
|
- training_steps: 1000
|
|
|
|
|
|
### Framework versions
|
|
|
|
|
|
- Transformers 4.51.0
|
|
|
- Pytorch 2.8.0+cu129
|
|
|
- Datasets 3.6.0
|
|
|
- Tokenizers 0.21.4
|
|
|
|
