Update README.md

README.md

@@ -1,3 +1,94 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- mozilla-foundation/common_voice_17_0
+language:
+- uz
+metrics:
+- wer
+library_name: transformers
+pipeline_tag: automatic-speech-recognition
+---
+language:
+- uz
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: Whisper Mediu, UZB - AISHA 
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 17.0
+      type: mozilla-foundation/common_voice_17_0
+      config: uz
+      split: None
+      args: 'config: uz, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 31.77905998468049
+---
+
+<!-- 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 UZB - AISHA
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2859
+- Wer: 31.7790
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.5187        | 0.5392 | 1000 | 0.4935          | 44.1403 |
+| 0.3423        | 1.0785 | 2000 | 0.4008          | 37.6948 |
+| 0.3018        | 1.6177 | 3000 | 0.3739          | 36.3575 |
+| 0.2401        | 2.1569 | 4000 | 0.2821          | 31.7791 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1