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---
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: Whisper Tiny English
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Minds 14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 0.258610624635143
---
<!-- 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 Tiny English
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Minds 14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4154
- Wer Ortho: 0.2659
- Wer: 0.2586
## 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: 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: 20
- training_steps: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 4.2901 | 0.33 | 5 | 4.2556 | 0.4220 | 0.2919 |
| 4.3552 | 0.67 | 10 | 3.7784 | 0.4226 | 0.2931 |
| 3.453 | 1.0 | 15 | 2.9546 | 0.4152 | 0.2907 |
| 2.9147 | 1.33 | 20 | 2.4090 | 0.3988 | 0.2931 |
| 2.3042 | 1.67 | 25 | 1.7869 | 0.3701 | 0.3001 |
| 1.6056 | 2.0 | 30 | 1.1284 | 0.3494 | 0.3012 |
| 0.988 | 2.33 | 35 | 0.6892 | 0.3860 | 0.3403 |
| 0.6605 | 2.67 | 40 | 0.5611 | 0.3128 | 0.2849 |
| 0.4645 | 3.0 | 45 | 0.4982 | 0.3091 | 0.2901 |
| 0.4884 | 3.33 | 50 | 0.4640 | 0.2963 | 0.2855 |
| 0.404 | 3.67 | 55 | 0.4453 | 0.2884 | 0.2814 |
| 0.4745 | 4.0 | 60 | 0.4268 | 0.2762 | 0.2697 |
| 0.303 | 4.33 | 65 | 0.4182 | 0.2829 | 0.2720 |
| 0.2717 | 4.67 | 70 | 0.4119 | 0.2829 | 0.2750 |
| 0.3464 | 5.0 | 75 | 0.4080 | 0.2860 | 0.2761 |
| 0.2193 | 5.33 | 80 | 0.4054 | 0.2823 | 0.2750 |
| 0.2138 | 5.67 | 85 | 0.4064 | 0.2762 | 0.2680 |
| 0.1571 | 6.0 | 90 | 0.4102 | 0.2799 | 0.2715 |
| 0.1398 | 6.33 | 95 | 0.4146 | 0.2768 | 0.2697 |
| 0.1523 | 6.67 | 100 | 0.4154 | 0.2659 | 0.2586 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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