update model card README.md

README.md

@@ -15,13 +15,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # BARTkrame-abstract
 
-This model is a fine-tuned version of [moussaKam/mbarthez](https://huggingface.co/moussaKam/mbarthez) on the None dataset.
+This model is a fine-tuned version of [krm/BARTkrame-abstract](https://huggingface.co/krm/BARTkrame-abstract) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.1454
-- Rouge1: 0.2588
-- Rouge2: 0.1200
-- Rougel: 0.2261
-- Rougelsum: 0.2272
+- Loss: 2.4196
+- Rouge1: 0.2703
+- Rouge2: 0.1334
+- Rougel: 0.2392
+- Rougelsum: 0.2419
 
 ## Model description
 
@@ -46,20 +46,16 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 8
+- num_epochs: 4
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
-|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
-| 1.9038        | 1.0   | 1250  | 1.5561          | 0.2519 | 0.1229 | 0.2178 | 0.2222    |
-| 1.2571        | 2.0   | 2500  | 1.5738          | 0.2610 | 0.1292 | 0.2236 | 0.2271    |
-| 0.8214        | 3.0   | 3750  | 1.6332          | 0.2529 | 0.1203 | 0.2170 | 0.2198    |
-| 0.5215        | 4.0   | 5000  | 1.8092          | 0.2397 | 0.1025 | 0.2051 | 0.2067    |
-| 0.3168        | 5.0   | 6250  | 1.9376          | 0.2655 | 0.1324 | 0.2305 | 0.2329    |
-| 0.1879        | 6.0   | 7500  | 2.0258          | 0.2618 | 0.1267 | 0.2282 | 0.2298    |
-| 0.1142        | 7.0   | 8750  | 2.1103          | 0.2615 | 0.1278 | 0.2282 | 0.2300    |
-| 0.0725        | 8.0   | 10000 | 2.1454          | 0.2588 | 0.1200 | 0.2261 | 0.2272    |
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
+| 0.1316        | 1.0   | 1250 | 2.3251          | 0.2505 | 0.1158 | 0.2150 | 0.2184    |
+| 0.0894        | 2.0   | 2500 | 2.3467          | 0.2526 | 0.1073 | 0.2067 | 0.2124    |
+| 0.045         | 3.0   | 3750 | 2.3742          | 0.2593 | 0.1211 | 0.2281 | 0.2308    |
+| 0.0242        | 4.0   | 5000 | 2.4196          | 0.2703 | 0.1334 | 0.2392 | 0.2419    |
 
 
 ### Framework versions