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---
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
- indonesian-nlp/librivox-indonesia
- mozilla-foundation/common_voice_11_0
metrics:
- wer
- cer
model-index:
- name: Whisper Medium ID - FLEURS-CV-LBV - Augmented
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: id
split: test
args: id
metrics:
- type: wer
value: 7.613206677118879
name: Wer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: id_id
split: test
metrics:
- type: wer
value: 7.17
name: WER
- type: cer
value: 2.39
name: CER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: id
split: test
metrics:
- type: wer
value: 7.59
name: WER
- type: cer
value: 2.33
name: CER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: indonesian-nlp/librivox-indonesia
type: indonesian-nlp/librivox-indonesia
config: ind
split: test
metrics:
- type: wer
value: 6.07
name: WER
- type: cer
value: 1.84
name: CER
---
<!-- 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 Medium ID - FLEURS-CV-LBV - Augmented
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the:
- [mozilla-foundation/common_voice_11_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0)
- [google/fleurs](https://huggingface.co/datasets/google/fleurs)
- [indonesian-nlp/librivox-indonesia](https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia) datasets.
It achieves the following results on the evaluation set (Common Voice 11.0):
- Loss: 0.2788
- Wer: 7.6132
- Cer: 2.3332
## 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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.3002 | 1.9 | 1000 | 0.1659 | 8.1850 | 2.5333 |
| 0.0514 | 3.8 | 2000 | 0.1818 | 8.0559 | 2.5244 |
| 0.0145 | 5.7 | 3000 | 0.2150 | 7.8945 | 2.5281 |
| 0.0037 | 7.6 | 4000 | 0.2248 | 7.7100 | 2.3738 |
| 0.0016 | 9.51 | 5000 | 0.2402 | 7.6224 | 2.3591 |
| 0.0009 | 11.41 | 6000 | 0.2525 | 7.7654 | 2.3952 |
| 0.0005 | 13.31 | 7000 | 0.2609 | 7.5994 | 2.3487 |
| 0.0008 | 15.21 | 8000 | 0.2682 | 7.5855 | 2.3347 |
| 0.0002 | 17.11 | 9000 | 0.2756 | 7.6178 | 2.3288 |
| 0.0002 | 19.01 | 10000 | 0.2788 | 7.6132 | 2.3332 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|