update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- generator
+metrics:
+- wer
+model-index:
+- name: ASR-whisper-small-1
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: generator
+      type: generator
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.49970056294166965
+---
+
+<!-- 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. -->
+
+# ASR-whisper-small-1
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the generator dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9304
+- Wer: 0.4997
+
+## 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: 0.0005
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 700
+- training_steps: 3000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 1.6949        | 0.33  | 1000 | 1.6964          | 0.9265 |
+| 0.9422        | 1.31  | 2000 | 1.1670          | 0.7292 |
+| 0.4947        | 2.28  | 3000 | 0.9304          | 0.4997 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.0
+- Datasets 2.14.4
+- Tokenizers 0.13.3