metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny_en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 0.36304909560723514
whisper-tiny_en
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6349
- Wer Ortho: 0.3964
- Wer: 0.3630
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 300
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
3.8643 | 1.79 | 50 | 3.5786 | 0.5114 | 0.3714 |
2.4042 | 3.57 | 100 | 2.3266 | 0.4657 | 0.3689 |
1.4319 | 5.36 | 150 | 1.3619 | 0.4367 | 0.3702 |
0.7558 | 7.14 | 200 | 0.7935 | 0.4213 | 0.3721 |
0.524 | 8.93 | 250 | 0.6820 | 0.4078 | 0.3721 |
0.4702 | 10.71 | 300 | 0.6349 | 0.3964 | 0.3630 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3