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---
language:
- pt
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny PT with Common Voice 11
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
args: 'config: pt, split: test'
metrics:
- name: Wer
type: wer
value: 33.24473522796974
---
<!-- 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 PT with Common Voice 11
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5205
- Wer: 33.2447
## 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: 8
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 16000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3154 | 0.44 | 1000 | 0.4987 | 36.2196 |
| 0.3252 | 0.88 | 2000 | 0.4586 | 33.6213 |
| 0.1989 | 1.32 | 3000 | 0.4457 | 32.7455 |
| 0.3112 | 1.76 | 4000 | 0.4356 | 31.4097 |
| 0.1329 | 2.2 | 5000 | 0.4348 | 31.1559 |
| 0.1193 | 2.64 | 6000 | 0.4343 | 31.4046 |
| 0.0723 | 3.07 | 7000 | 0.4424 | 31.5869 |
| 0.0698 | 3.51 | 8000 | 0.4497 | 32.0827 |
| 0.0865 | 3.95 | 9000 | 0.4497 | 31.0945 |
| 0.0522 | 4.39 | 10000 | 0.4716 | 32.2190 |
| 0.0542 | 4.83 | 11000 | 0.4761 | 32.6944 |
| 0.061 | 5.27 | 12000 | 0.4983 | 32.0691 |
| 0.0459 | 5.71 | 13000 | 0.4985 | 32.4968 |
| 0.0338 | 6.15 | 14000 | 0.5123 | 33.3129 |
| 0.0492 | 6.59 | 15000 | 0.5217 | 33.2686 |
| 0.0194 | 7.03 | 16000 | 0.5205 | 33.2447 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1
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