Update README.md

README.md

@@ -11,7 +11,7 @@ base_model:
 # Model Card for Model ID
 
  it was used to fine-tune OuteAI/Lite-Oute-1-300M-Instruct for tweet tone classification problem.
- Default model achieved 0.08 f1-score, while fine-tuned version achieved 0.53 f1-score in less than 8 minutes of fine-tuning on a single A100
+ Default model achieved 0.08 f1-score, while fine-tuned version achieved 0.51 f1-score in less than 15 minutes of fine-tuning on a single A100
 
 
 #### Prameters
@@ -22,7 +22,7 @@ DoRA was used with r=8 and alpha=16 to fine-tune "k_proj", "v_proj".
 #### Training parameters
 BATCH_SIZE = 32
 LEARNING_RATE = 3e-4
-NUM_EPOCHS = 1
+NUM_EPOCHS = 2
 
 
 #### Metrics