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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper tiny en-US - J3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14-en-US
type: PolyAI/minds14
config: en-US
split: train[450:]
args: en-US
metrics:
- name: Wer
type: wer
value: 0.3654073199527745
---
<!-- 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 en-US - J3
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14-en-US dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0413
- Wer Ortho: 0.3603
- Wer: 0.3654
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 100
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.0001 | 35.71 | 500 | 0.8505 | 0.3430 | 0.3459 |
| 0.0 | 71.43 | 1000 | 0.9093 | 0.3455 | 0.3501 |
| 0.0 | 107.14 | 1500 | 0.9707 | 0.3553 | 0.3589 |
| 0.0 | 142.86 | 2000 | 1.0413 | 0.3603 | 0.3654 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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