Update README.md

README.md

@@ -38,7 +38,6 @@ int2str = {
 str2int = {v:k for k,v in int2str.items()}
 
 # Load model dependencies
-
 model = AutoModelForTokenClassification.from_pretrained(
     "brolaurens/finer-distilbert", num_labels=len(int2str), id2label=int2str, label2id=str2int
 )
@@ -57,6 +56,18 @@ model_input = tokenizer(texts, return_tensors='pt')
 predictions = model(**model_input).logits
 predictions = predictions.argmax(axis=2)
 predicted_labels = [[int2str[x] for x in t] for t in predictions.tolist()]
+```
+
+## Training parameters
 
+The model was trained using the following hyperparameters:
 
-```
+base_model: distilbert/distilbert-base-uncased
+learning_rate: 2e-5
+batch_size: 32
+epochs: 3
+optimizer: adamw
+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1e-08
+loss_function: cross entropy loss