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---
language:
- pt
license: apache-2.0
base_model: openai/whisper-large
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large Portuguese
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 pt
type: mozilla-foundation/common_voice_13_0
config: pt
split: test
args: pt
metrics:
- name: Wer
type: wer
value: 6.399303387769856
---
<!-- 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 Large Portuguese
This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_13_0 pt dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4799
- Wer: 6.3993
## 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-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.077 | 3.53 | 1000 | 0.1616 | 5.4957 |
| 0.0155 | 7.05 | 2000 | 0.2549 | 6.1956 |
| 0.0045 | 10.58 | 3000 | 0.3122 | 5.9261 |
| 0.0017 | 14.11 | 4000 | 0.3317 | 6.0099 |
| 0.0018 | 17.64 | 5000 | 0.3604 | 6.0099 |
| 0.0009 | 21.16 | 6000 | 0.3779 | 6.1791 |
| 0.0012 | 24.69 | 7000 | 0.3470 | 6.0066 |
| 0.0013 | 28.22 | 8000 | 0.3838 | 6.1479 |
| 0.0007 | 31.75 | 9000 | 0.3839 | 6.0395 |
| 0.0003 | 35.27 | 10000 | 0.4090 | 6.2054 |
| 0.0003 | 38.8 | 11000 | 0.4053 | 6.2859 |
| 0.0002 | 42.33 | 12000 | 0.4235 | 6.3467 |
| 0.0002 | 45.86 | 13000 | 0.4326 | 6.3500 |
| 0.0001 | 49.38 | 14000 | 0.4415 | 6.3714 |
| 0.0001 | 52.91 | 15000 | 0.4506 | 6.3878 |
| 0.0001 | 56.44 | 16000 | 0.4586 | 6.4092 |
| 0.0001 | 59.96 | 17000 | 0.4663 | 6.3944 |
| 0.0001 | 63.49 | 18000 | 0.4730 | 6.3911 |
| 0.0001 | 67.02 | 19000 | 0.4778 | 6.3944 |
| 0.0001 | 70.55 | 20000 | 0.4799 | 6.3993 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.15.1
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