Update README.md

README.md

@@ -36,7 +36,7 @@ It achieves the following results on the evaluation set:
 - F1: 95.084
 - Gen Len: 2.4976
 
-```
+```cmd
               precision    recall  f1-score   support
 
            0       0.97      0.88      0.92     12500
@@ -56,12 +56,12 @@ This model was trained on the imdb train dataset with 25,000 data and then teste
 
 ## Usage
 
-- Install dependencies
+1. Install dependencies
 ```python
 !pip install transformers==4.28.1 datasets
 ```
 
-- Load IMDB Corpus
+2. Load IMDB Corpus
 ```python
 from datasets import load_dataset
 
@@ -71,7 +71,7 @@ dataset_id = "imdb"
 dataset = load_dataset(dataset_id)
 ```
 
-- Load fine tune flan t5 model
+3. Load fine tune flan t5 model
 ```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 tokenizer = AutoTokenizer.from_pretrained("mohammadtaghizadeh/flan-t5-base-imdb-text-classification")
@@ -79,7 +79,7 @@ model = AutoModelForSeq2SeqLM.from_pretrained("mohammadtaghizadeh/flan-t5-base-i
 model.to('cuda')
 ```
 
-- Test the model
+4. Test the model
 ```python
 from tqdm.auto import tqdm
 
@@ -98,7 +98,7 @@ for i in range(samples_number):
   progress_bar.update(1)
 ```
 
-- Classification report
+5. Classification report
 ```python
 from sklearn.metrics import classification_report
 
@@ -109,7 +109,7 @@ report = classification_report(str_labels_list, predictions_list)
 print(report)
 ```
 
-- Output
+Output
 ```cmd
               precision    recall  f1-score   support