update model card README.md

README.md

@@ -1,41 +1,38 @@
 ---
-language:
-- id
 license: apache-2.0
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_11_0
+- common_voice_11_0
 metrics:
 - wer
 model-index:
-- name: Whisper Tiny Indonesian
+- name: whisper-tiny-id
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: mozilla-foundation/common_voice_11_0 id
-      type: mozilla-foundation/common_voice_11_0
+      name: common_voice_11_0
+      type: common_voice_11_0
       config: id
-      split: train
+      split: test
       args: id
     metrics:
     - name: Wer
       type: wer
-      value: 145.78068800147562
+      value: 33.344092963202066
 ---
 
 <!-- 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 Indonesian
+# whisper-tiny-id
 
-This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 id dataset.
+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: 1.8237
-- Wer: 145.7807
+- Loss: 0.7428
+- Wer: 33.3441
 
 ## Model description
 
@@ -55,25 +52,34 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 64
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 4
-- training_steps: 10
+- lr_scheduler_warmup_steps: 500
+- training_steps: 5000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer      |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.0002        | 0.02  | 6    | 1.8237          | 145.7807 |
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.3823        | 4.95  | 500  | 0.5251          | 33.4732 |
+| 0.0495        | 9.9   | 1000 | 0.5700          | 33.3902 |
+| 0.0077        | 14.85 | 1500 | 0.6202          | 32.4218 |
+| 0.0031        | 19.8  | 2000 | 0.6616          | 32.5371 |
+| 0.0019        | 24.75 | 2500 | 0.6873          | 32.7954 |
+| 0.0014        | 29.7  | 3000 | 0.7056          | 33.5700 |
+| 0.0011        | 34.65 | 3500 | 0.7204          | 33.7960 |
+| 0.0009        | 39.6  | 4000 | 0.7327          | 33.7729 |
+| 0.0008        | 44.55 | 4500 | 0.7400          | 33.9113 |
+| 0.0007        | 49.5  | 5000 | 0.7428          | 33.3441 |
 
 
 ### Framework versions
 
-- Transformers 4.25.1
-- Pytorch 1.12.1
-- Datasets 2.7.1
-- Tokenizers 0.13.1
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1.dev0
+- Tokenizers 0.13.2