metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-minds14-en-v2
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: 0.3695395513577332
whisper-tiny-finetuned-minds14-en-v2
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: 0.7064
- Wer Ortho: 0.3720
- Wer: 0.3695
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: 64
- 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: 500
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
1.5939 | 7.14 | 50 | 0.6729 | 0.4294 | 0.4032 |
0.1094 | 14.29 | 100 | 0.5254 | 0.3763 | 0.3642 |
0.0057 | 21.43 | 150 | 0.5993 | 0.3646 | 0.3607 |
0.002 | 28.57 | 200 | 0.6255 | 0.3609 | 0.3601 |
0.0013 | 35.71 | 250 | 0.6444 | 0.3652 | 0.3625 |
0.0009 | 42.86 | 300 | 0.6603 | 0.3689 | 0.3660 |
0.0007 | 50.0 | 350 | 0.6736 | 0.3701 | 0.3678 |
0.0006 | 57.14 | 400 | 0.6857 | 0.3726 | 0.3707 |
0.0005 | 64.29 | 450 | 0.6965 | 0.3708 | 0.3689 |
0.0004 | 71.43 | 500 | 0.7064 | 0.3720 | 0.3695 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3