Update README.md

README.md

@@ -1,13 +1,13 @@
 ---
-library_name: transformers
-tags: []
+library_name: transformers, peft, torch
+tags: [asr, whisper, finetune, atc, aircraft, communications, english]
 ---
 
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-
+[SUMMARY HERE]
 
 ## Model Details
 
@@ -15,8 +15,6 @@ tags: []
 
 <!-- Provide a longer summary of what this model is. -->
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
 - **Developed by:** Jesse Arzate
 - **Model type:** Sequence-to-Sequence (Seq2Seq) Transformer-based model
 - **Language(s) (NLP):** English
@@ -117,9 +115,6 @@ df_subset = pd.concat([df_subset, transcriptions_finetuned], axis=1)
 Dataset: ATC audio recordings from actual flight operations.
 Size: ~250 hours of annotated data.
 
-
-[More Information Needed]
-
 ### Training Procedure
 
 <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
@@ -182,13 +177,11 @@ Randomly sampled 20% of the data with seed = 42.
 
 <!-- These are the evaluation metrics being used, ideally with a description of why. -->
 
-Word Error Rate
-Normalized Word Error Rate
+Word Error Rate, Normalized Word Error Rate
 
 ### Results
 
-Mean WER for 500 test samples: 0.145
-  with 95% confidence interval: (0.123, 0.167)
+Mean WER for 500 test samples: 0.145 with 95% confidence interval: (0.123, 0.167)
 
 #### Summary
 
@@ -219,10 +212,10 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 #### Hardware
 
-CPU: AMD EPYC 7313P 16-Core Processor 3.00 GHz
-GPU: NVIDIA RTX A2000
-vRAM: 6GB
-RAM: 128GB
+- **CPU**: AMD EPYC 7313P 16-Core Processor 3.00 GHz
+- **GPU**: NVIDIA RTX A2000
+- **vRAM**: 6GB
+- **RAM**: 128GB
 
 #### Software