Upload README.md

README.md

@@ -0,0 +1,77 @@
+---
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- generated_from_trainer
+datasets:
+- Prajwal-143/ASR-Tamil-cleaned
+metrics:
+- wer
+model-index:
+- name: Whisper-med-eng-Log-english
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: ' asr-tamil-cleaned'
+      type: Prajwal-143/ASR-Tamil-cleaned
+    metrics:
+    - name: Wer
+      type: wer
+      value: 10.398363506699864
+---
+
+<!-- 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-med-eng - Log-english
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the  asr-tamil-cleaned dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1642
+- Wer Ortho: 36.6838
+- Wer: 10.3984
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant_with_warmup
+- lr_scheduler_warmup_steps: 50
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
+| 0.1613        | 0.0143 | 500  | 0.1642          | 36.6838   | 10.3984 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1