metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- localdataset
metrics:
- wer
model-index:
- name: testing
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: localdataset
type: localdataset
config: default
split: test
args: 'config: data, split: test'
metrics:
- name: Wer
type: wer
value: 0
testing
This model is a fine-tuned version of openai/whisper-small on the localdataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 62
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0 | 125.0 | 125 | 0.0000 | 0.0 |
| 0.0 | 250.0 | 250 | 0.0000 | 0.0 |
| 0.0 | 375.0 | 375 | 0.0000 | 0.0 |
| 0.0 | 500.0 | 500 | 0.0000 | 0.0 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3