update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- dataset_whisper
+metrics:
+- wer
+model-index:
+- name: Transcriber-Medium
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: dataset_whisper
+      type: dataset_whisper
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 108.52032520325203
+---
+
+<!-- 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. -->
+
+# Transcriber-Medium
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the dataset_whisper dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.9360
+- Wer: 108.5203
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- 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: 200
+- training_steps: 100
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer      |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.7536        | 4.02  | 100  | 2.9360          | 108.5203 |
+
+
+### Framework versions
+
+- Transformers 4.32.0.dev0
+- Pytorch 1.12.1+cu113
+- Datasets 2.14.1
+- Tokenizers 0.13.3