Update README.md

README.md

@@ -27,54 +27,51 @@ model-index:
       value: 5.590020342630419
 ---
 
-<!-- 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 V2 Portuguese 🇧🇷🇵🇹
 
-# Whisper Large v2 Portuguese
+Bem-vindo ao **whisper large-v2** para transcrição em português 👋🏻
 
-This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 pt dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2821
-- Wer: 5.5900
+Transcribe Portuguese audio to text with the highest precision.
 
-## Model description
+- Loss: 0.282
+- Wer: 5.590
 
-More information needed
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the [mozilla-foundation/common_voice_11](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) dataset. If you want a lighter model, you may be interested in [jlondonobo/whisper-medium-pt](https://huggingface.co/jlondonobo/whisper-medium-pt). It achieves faster inference with almost no difference in WER.
 
-## Intended uses & limitations
+### Comparable models
+Reported **WER** is based on the evaluation subset of Common Voice.
+| Model                                            | WER    | # Parameters |
+|--------------------------------------------------|:--------:|:------------:|
+| [jlondonobo/whisper-large-v2-pt](https://huggingface.co/jlondonobo/whisper-large-v2-pt)                     | **5.590** 🤗  | 1550M       |
+| [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2)                            | 6.300   | 1550M       |
+| [jlondonobo/whisper-medium-pt](https://huggingface.co/jlondonobo/whisper-medium-pt)                            | 6.579   | 769M       |
+| [jonatasgrosman/wav2vec2-large-xlsr-53-portuguese](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese) | 11.310  | 317M       |
+| [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese)    | 20.080 | 317M       |
 
-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: 8
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- training_steps: 5000
-- mixed_precision_training: Native AMP
+We used the following hyperparameters for training:
+- `learning_rate`: 1e-05
+- `train_batch_size`: 16
+- `eval_batch_size`: 8
+- `seed`: 42
+- `gradient_accumulation_steps`: 2
+- `total_train_batch_size`: 32
+- `optimizer`: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- `lr_scheduler_type`: linear
+- `lr_scheduler_warmup_steps`: 500
+- `training_steps`: 5000
+- `mixed_precision_training`: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.0828        | 1.09  | 1000 | 0.1868          | 6.7786 |
-| 0.0241        | 3.07  | 2000 | 0.2057          | 6.1095 |
-| 0.0084        | 5.06  | 3000 | 0.2367          | 6.0288 |
-| 0.0015        | 7.04  | 4000 | 0.2469          | 5.7094 |
-| 0.0009        | 9.02  | 5000 | 0.2821          | 5.5900 |
+| 0.0828        | 1.09  | 1000 | 0.1868          | 6.778 |
+| 0.0241        | 3.07  | 2000 | 0.2057          | 6.109 |
+| 0.0084        | 5.06  | 3000 | 0.2367          | 6.029 |
+| 0.0015        | 7.04  | 4000 | 0.2469          | 5.709 |
+| 0.0009        | 9.02  | 5000 | 0.2821          | 5.590 🤗|
 
 
 ### Framework versions