Update README.md

README.md

@@ -6,33 +6,25 @@ tags:
 metrics:
 - accuracy
 model-index:
-- name: 1e05_output_dir_clean_df_10-100_noX_100_50_epoch_cluster
+- name: AmpGPT2
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# 1e05_output_dir_clean_df_10-100_noX_100_50_epoch_cluster
+# AmpGPT2
 
-This model is a fine-tuned version of [nferruz/ProtGPT2](https://huggingface.co/nferruz/ProtGPT2) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 3.9890
-- Accuracy: 0.4213
+AmpGPT2 is a language model capable of generating de novo antimicrobial peptides (AMPs). Generated sequences are predicted to be AMPs 95.83% of the time.
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
+AmpGPT2 is a fine-tuned version of [nferruz/ProtGPT2](https://huggingface.co/nferruz/ProtGPT2) based on the GPT2 Transformer architecture. 
+To validate the results the Antimicrobial Peptide Scanner vr.2 (https://www.dveltri.com/ascan/v2/ascan.html) was used. It is a 
 
 ## Training and evaluation data
 
-More information needed
-
-## Training procedure
+run_clm.py
 
 ### Training hyperparameters
 
@@ -46,58 +38,10 @@ The following hyperparameters were used during training:
 - num_epochs: 50.0
 
 ### Training results
+tr
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 148  | 5.8378          | 0.2287   |
-| No log        | 2.0   | 296  | 5.5732          | 0.2491   |
-| No log        | 3.0   | 444  | 5.3800          | 0.2680   |
-| 5.761         | 4.0   | 592  | 5.2259          | 0.2842   |
-| 5.761         | 5.0   | 740  | 5.1006          | 0.2963   |
-| 5.761         | 6.0   | 888  | 4.9997          | 0.3067   |
-| 5.1725        | 7.0   | 1036 | 4.9103          | 0.3153   |
-| 5.1725        | 8.0   | 1184 | 4.8287          | 0.3230   |
-| 5.1725        | 9.0   | 1332 | 4.7578          | 0.3301   |
-| 5.1725        | 10.0  | 1480 | 4.6942          | 0.3376   |
-| 4.8482        | 11.0  | 1628 | 4.6364          | 0.3439   |
-| 4.8482        | 12.0  | 1776 | 4.5813          | 0.3497   |
-| 4.8482        | 13.0  | 1924 | 4.5328          | 0.3554   |
-| 4.609         | 14.0  | 2072 | 4.4897          | 0.3610   |
-| 4.609         | 15.0  | 2220 | 4.4454          | 0.3657   |
-| 4.609         | 16.0  | 2368 | 4.4132          | 0.3702   |
-| 4.4241        | 17.0  | 2516 | 4.3742          | 0.3738   |
-| 4.4241        | 18.0  | 2664 | 4.3438          | 0.3782   |
-| 4.4241        | 19.0  | 2812 | 4.3164          | 0.3817   |
-| 4.4241        | 20.0  | 2960 | 4.2879          | 0.3848   |
-| 4.283         | 21.0  | 3108 | 4.2602          | 0.3878   |
-| 4.283         | 22.0  | 3256 | 4.2373          | 0.3902   |
-| 4.283         | 23.0  | 3404 | 4.2160          | 0.3932   |
-| 4.1606        | 24.0  | 3552 | 4.1964          | 0.3954   |
-| 4.1606        | 25.0  | 3700 | 4.1816          | 0.3976   |
-| 4.1606        | 26.0  | 3848 | 4.1605          | 0.3995   |
-| 4.1606        | 27.0  | 3996 | 4.1443          | 0.4016   |
-| 4.0685        | 28.0  | 4144 | 4.1290          | 0.4034   |
-| 4.0685        | 29.0  | 4292 | 4.1146          | 0.4052   |
-| 4.0685        | 30.0  | 4440 | 4.1037          | 0.4067   |
-| 3.9859        | 31.0  | 4588 | 4.0874          | 0.4082   |
-| 3.9859        | 32.0  | 4736 | 4.0784          | 0.4098   |
-| 3.9859        | 33.0  | 4884 | 4.0669          | 0.4115   |
-| 3.9275        | 34.0  | 5032 | 4.0581          | 0.4125   |
-| 3.9275        | 35.0  | 5180 | 4.0479          | 0.4136   |
-| 3.9275        | 36.0  | 5328 | 4.0384          | 0.4148   |
-| 3.9275        | 37.0  | 5476 | 4.0330          | 0.4159   |
-| 3.8799        | 38.0  | 5624 | 4.0262          | 0.4166   |
-| 3.8799        | 39.0  | 5772 | 4.0212          | 0.4174   |
-| 3.8799        | 40.0  | 5920 | 4.0136          | 0.4180   |
-| 3.8348        | 41.0  | 6068 | 4.0111          | 0.4186   |
-| 3.8348        | 42.0  | 6216 | 4.0048          | 0.4193   |
-| 3.8348        | 43.0  | 6364 | 4.0004          | 0.4195   |
-| 3.8151        | 44.0  | 6512 | 3.9978          | 0.4199   |
-| 3.8151        | 45.0  | 6660 | 3.9951          | 0.4203   |
-| 3.8151        | 46.0  | 6808 | 3.9934          | 0.4207   |
-| 3.8151        | 47.0  | 6956 | 3.9904          | 0.4209   |
-| 3.7948        | 48.0  | 7104 | 3.9911          | 0.4211   |
-| 3.7948        | 49.0  | 7252 | 3.9890          | 0.4213   |
 | 3.7948        | 50.0  | 7400 | 3.9890          | 0.4213   |