update model card README.md

README.md

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+---
+language:
+- de
+license: apache-2.0
+tags:
+- sbb-asr
+- generated_from_trainer
+datasets:
+- marccgrau/sbbdata_allSNR
+metrics:
+- wer
+model-index:
+- name: Whisper Small German SBB all SNR - v2
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: SBB Dataset 05.01.2023
+      type: marccgrau/sbbdata_allSNR
+      args: 'config: German, split: train, test, val'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.18325935320228282
+---
+
+<!-- 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 Small German SBB all SNR - v2
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SBB Dataset 05.01.2023 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4018
+- Wer: 0.1833
+
+## 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: 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: 100
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 2.6097        | 0.71  | 100  | 0.9753          | 0.7838 |
+| 0.754         | 1.42  | 200  | 0.6018          | 0.6906 |
+| 0.5414        | 2.13  | 300  | 0.4864          | 0.5149 |
+| 0.4521        | 2.84  | 400  | 0.4234          | 0.2372 |
+| 0.4131        | 3.55  | 500  | 0.4018          | 0.1833 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.1
+- Datasets 2.8.0
+- Tokenizers 0.12.1