update model card README.md

README.md

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+---
+language:
+- pl
+license: apache-2.0
+tags:
+- whisper-event
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0
+- google/fleurs
+metrics:
+- wer
+model-index:
+- name: Whisper Medium PL
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0
+      type: mozilla-foundation/common_voice_11_0
+      config: pl
+      split: test
+      args: pl
+    metrics:
+    - name: Wer
+      type: wer
+      value: 8.68718413673836
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: FLEURS
+      type: google/fleurs
+    metrics:
+    - name: Wer
+      type: wer
+      value: 8.68718413673836
+---
+
+<!-- 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 Medium PL
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 and the FLEURS datasets.
+It achieves the following results on the evaluation set:
+- Loss: 0.3947
+- Wer: 8.6872
+
+## 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: 4
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 8
+- 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: 8000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0805        | 0.48  | 500  | 0.2556          | 10.4888 |
+| 0.0685        | 0.96  | 1000 | 0.2462          | 10.7608 |
+| 0.0356        | 1.45  | 1500 | 0.2561          | 9.6728  |
+| 0.0337        | 1.93  | 2000 | 0.2327          | 9.6459  |
+| 0.017         | 2.41  | 2500 | 0.2444          | 9.9464  |
+| 0.0179        | 2.9   | 3000 | 0.2554          | 9.6476  |
+| 0.0056        | 3.38  | 3500 | 0.3001          | 9.3638  |
+| 0.007         | 3.86  | 4000 | 0.2809          | 9.2245  |
+| 0.0033        | 4.34  | 4500 | 0.3235          | 9.3437  |
+| 0.0024        | 4.83  | 5000 | 0.3148          | 9.0633  |
+| 0.0008        | 5.31  | 5500 | 0.3416          | 9.0112  |
+| 0.0011        | 5.79  | 6000 | 0.3876          | 9.1858  |
+| 0.0004        | 6.27  | 6500 | 0.3745          | 8.7292  |
+| 0.0003        | 6.76  | 7000 | 0.3704          | 9.0314  |
+| 0.0003        | 7.24  | 7500 | 0.3929          | 8.6553  |
+| 0.0002        | 7.72  | 8000 | 0.3947          | 8.6872  |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1.dev0
+- Tokenizers 0.13.2