Update README.md

README.md

@@ -41,9 +41,6 @@ It achieves the following results on the evaluation set:
 
 More information needed
 
-## Intended uses & limitations
-
-More information needed
 
 ## Training and evaluation data
 
@@ -65,6 +62,35 @@ The following hyperparameters were used during training:
 - training_steps: 4000
 - mixed_precision_training: Native AMP
 
+``` %python
+from transformers import Seq2SeqTrainingArguments
+
+training_args = Seq2SeqTrainingArguments(
+    output_dir="./whisper-small-da", 
+    per_device_train_batch_size=16,
+    gradient_accumulation_steps=1,  
+    learning_rate=1e-5,
+    lr_scheduler_type="linear",
+    warmup_steps=50,
+    max_steps=4000,  
+    gradient_checkpointing=True,
+    fp16=True,
+    fp16_full_eval=True,
+    evaluation_strategy="steps",
+    per_device_eval_batch_size=16,
+    predict_with_generate=True,
+    generation_max_length=225,
+    save_steps=500,
+    eval_steps=500,
+    logging_steps=25,
+    report_to=["tensorboard"],
+    load_best_model_at_end=True,
+    metric_for_best_model="wer",
+    greater_is_better=False,
+    push_to_hub=True,
+)
+```
+
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |