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---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-test-finetuned
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-AU
split: train
args: en-AU
metrics:
- name: Wer
type: wer
value: 14.926022628372499
---
<!-- 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-minds14-test-finetuned
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5522
- Wer Ortho: 15.9236
- Wer: 14.9260
## 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: 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.0009 | 15.15 | 500 | 0.4051 | 14.5587 | 13.5335 |
| 0.0003 | 30.3 | 1000 | 0.4404 | 14.8772 | 13.7511 |
| 0.0002 | 45.45 | 1500 | 0.4655 | 15.5596 | 14.4909 |
| 0.0001 | 60.61 | 2000 | 0.4870 | 15.4231 | 14.3168 |
| 0.0001 | 75.76 | 2500 | 0.5048 | 15.6961 | 14.6649 |
| 0.0 | 90.91 | 3000 | 0.5217 | 15.7871 | 14.7084 |
| 0.0 | 106.06 | 3500 | 0.5368 | 15.9691 | 14.9260 |
| 0.0 | 121.21 | 4000 | 0.5522 | 15.9236 | 14.9260 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2
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