Update README.md

README.md

@@ -18,9 +18,10 @@ AmpGPT2 is a language model capable of generating de novo antimicrobial peptides
 
 AmpGPT2 is a fine-tuned version of [nferruz/ProtGPT2](https://huggingface.co/nferruz/ProtGPT2) based on the GPT2 Transformer architecture. 
 
-| Training Loss | Epoch | Validation Loss | Accuracy |
-|:-------------:|:-----:|:---------------:|:--------:|
-| 3.7948        | 50.0  | 3.9890          | 0.4213   |
+| Model | sequences generated | Amp% | average length |
+|:------------:|:-----------:|:-----------:|:-----------:|
+| AmpGPT2| 1000 | 95.86| 64.08   |
+| ProtGPT2| 1000 | 51.85 | 222.59 |
 
 To validate the results the Antimicrobial Peptide Scanner vr.2 (https://www.dveltri.com/ascan/v2/ascan.html) was used, which is a deep learning tool specifically designed for AMP recognition.
 
@@ -62,24 +63,9 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 50.0
 
-\begin{table}[h!]
-    \centering
-    \caption{AMP Yield Comparison between AmpGPT2 and ProtGPT2}
-    \begin{tabular}{lccc}
-        \toprule
-        Model & Total Sequences & AMP Classified & AMP Percentage (AMP\%) \\
-        \midrule
-        AmpGPT2 & 10000 & 9541 & 95.41\% \\
-        ProtGPT2 & 10000 & 5530 & 55.3\% \\
-        \bottomrule
-    \end{tabular}
-    \label{tab:amp_yield}
-\end{table}
-
-| Model | Amp% | Length |
-|:-------:|:-----:|:-------:|
-|AmpGPT2|95.86|64.08   |
-|ProtGPT2| 51.85 | 222.59 |
+| Training Loss | Epoch | Validation Loss | Accuracy |
+|:-------------:|:-----:|:---------------:|:--------:|
+| 3.7948        | 50.0  | 3.9890          | 0.4213   |
 
 ### Framework versions