update model card README.md

README.md

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+---
+language:
+- de
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: whisper-fine-tuned-de_learn
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0
+      type: mozilla-foundation/common_voice_11_0
+      config: de
+      split: test[:2000]
+      args: 'config: german, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 19.79678045438977
+---
+
+<!-- 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-fine-tuned-de_learn
+
+This model is a fine-tuned version of [whisper-fine-tuned-de_arg_new](https://huggingface.co/whisper-fine-tuned-de_arg_new) on the Common Voice 11.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4825
+- Wer: 19.7968
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- 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     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.1169        | 1.6   | 1000 | 0.4126          | 20.2477 |
+| 0.0132        | 3.2   | 2000 | 0.4562          | 20.4304 |
+| 0.0053        | 4.8   | 3000 | 0.4647          | 20.0480 |
+| 0.0016        | 6.4   | 4000 | 0.4775          | 19.8082 |
+| 0.0011        | 8.0   | 5000 | 0.4825          | 19.7968 |
+
+
+### Framework versions
+
+- Transformers 4.28.0.dev0
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3