Merge branch 'main' of https://huggingface.co/jonatasgrosman/whisper-large-pt-cv11 into main

README.md

@@ -39,49 +39,3 @@ This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingf
 It achieves the following results on the evaluation set:
 - WER: 4.816664144852979
 - CER: 1.6052355927195898
-
-## 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: 5e-06
-- 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: 2000
-- training_steps: 20000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
-| 0.1051        | 1.24  | 1000 | 0.1501          | 5.1922 | 1.5979 |
-| 0.0682        | 2.47  | 2000 | 0.1589          | 5.7523 | 1.8633 |
-| 0.0489        | 3.71  | 3000 | 0.1631          | 5.3588 | 1.6819 |
-| 0.0309        | 4.94  | 4000 | 0.1707          | 5.2831 | 1.6819 |
-
-
-### Framework versions
-
-- Transformers 4.26.0.dev0
-- Pytorch 1.13.1+cu117
-- Datasets 2.7.1.dev0
-- Tokenizers 0.13.2