Update app.py

app.py

@@ -43,7 +43,7 @@ st.sidebar.write("""
 7. **Performance Note:**
    - The model's performance varies due to its size and training data. It performs best on text generation and translation.
    - For other tasks, try multiple times if model's output is not optimal (This is due to the generator's sampling parameter settings).
-   - It's best to read/understand/translate the model's output completely first. Model can sometimes fail to stop generation after providing correct answers.
+   - **It's best to read/understand/translate the model's output completely first. Model can sometimes fail to stop generation after providing correct answers.**
 8. **Other Tips:**
    - Use simple instructions for instruction following.
    - For question answering and generation, follow the structure in the corresponding sample text.
@@ -53,7 +53,7 @@ st.sidebar.write("""
 """)
 
 max_length = 100 
-max_new_tokens = 50
+max_new_tokens = 80
 num_beams = 5
 temperature = 0.99 
 top_k = 50
@@ -90,7 +90,7 @@ st.title("SabiYarn-125M : Generates text in multiple Nigerian languages.")
 st.write("**Supported Languages: English, Yoruba, Igbo, Hausa, Pidgin, Efik, Urhobo, Fulfulde, Fulah. \nResults may not be coherent for less represented languages (i.e Efik, \
 Urhobo, Fulfulde, Fulah).**")
 st.write("**It takes a while (~25s) to return an output on the first 'generate' click. Avg response time: 1-2s on GPU, 40s on CPU**")
-st.write("**Model outputs 50 tokens as default. Adjust in the side bar.**")
+st.write("**Model outputs 80 tokens as default. Adjust in the side bar.**")
 st.write("**For convenience, you can use chatgpt to provide input text and translate/evaluate model output.**")
 st.write("-" * 50)
 popular_topics = [
@@ -266,11 +266,11 @@ if st.button("Generate"):
             print("Generated text: ", generated_text)
             
             if task == "Sentiment Classification" :
-                if generated_text.strip().lower().startswith("negative"):
+                if "negative" in generated_text.lower():
                     generated_text = "Negative"
-                elif generated_text.strip().lower().startswith("positive"):
+                elif "positive" in generated_text.lower():
                     generated_text = "Positive"
-                elif generated_text.strip().lower().startswith("neutral"):
+                elif "neutral" in generated_text.lower():
                     generated_text = "Neutral"
     
             elif task == "Topic Classification":
@@ -281,6 +281,7 @@ if st.button("Generate"):
                 
             elif task == "Translation":
                 n_sentences = len(re.split(r"\.|\n", user_input))
+                print("split for translation: ",re.split(r"\.|\n", generated_text)[:n_sentences])
                 generated_text = ".".join(re.split(r"\.|\n", generated_text)[:n_sentences])
                     
             full_output = st.empty()