update model card README.md

README.md

@@ -15,11 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0](https://huggingface.co/JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4253
-- Bleu: 95.481
-- Em: 0.6019
-- Rm: 0.6547
-- Gen Len: 80.4676
+- Loss: 0.3523
+- Bleu: 95.2821
+- Em: 0.1415
+- Rm: 0.3046
+- Gen Len: 58.7746
 
 ## Model description
 
@@ -39,25 +39,41 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 64
-- eval_batch_size: 16
+- train_batch_size: 32
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 2000
 - num_epochs: 300.0
-- mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Bleu    | Em     | Rm     | Gen Len |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:-------:|
-| 2.9129        | 50.0  | 1000 | 0.3861          | 92.7571 | 0.2302 | 0.2422 | 79.2806 |
-| 0.052         | 100.0 | 2000 | 0.3532          | 95.3257 | 0.5156 | 0.5635 | 80.6859 |
-| 0.0155        | 150.0 | 3000 | 0.4280          | 94.8017 | 0.5659 | 0.6355 | 79.3165 |
-| 0.0086        | 200.0 | 4000 | 0.4077          | 95.5885 | 0.5803 | 0.6283 | 80.6978 |
-| 0.0051        | 250.0 | 5000 | 0.4169          | 95.5923 | 0.6019 | 0.6523 | 80.6523 |
-| 0.0038        | 300.0 | 6000 | 0.4253          | 95.481  | 0.6019 | 0.6547 | 80.4676 |
+| Training Loss | Epoch  | Step  | Bleu    | Em     | Gen Len | Validation Loss | Rm     |
+|:-------------:|:------:|:-----:|:-------:|:------:|:-------:|:---------------:|:------:|
+| 4.0279        | 12.82  | 500   | 49.841  | 0.0    | 51.6403 | 2.4031          | 0.0    |
+| 1.3442        | 25.64  | 1000  | 85.0177 | 0.0    | 57.9784 | 0.5014          | 0.0    |
+| 0.2522        | 38.46  | 1500  | 94.0714 | 0.0168 | 57.9137 | 0.3293          | 0.0216 |
+| 0.1534        | 51.28  | 2000  | 94.4328 | 0.0024 | 58.9448 | 0.3207          | 0.0072 |
+| 0.1305        | 64.1   | 2500  | 94.0708 | 0.0    | 59.6115 | 0.3247          | 0.0    |
+| 0.1226        | 76.92  | 3000  | 94.3143 | 0.0024 | 58.235  | 0.3325          | 0.0024 |
+| 0.1131        | 89.74  | 3500  | 94.5678 | 0.0048 | 59.6811 | 0.3401          | 0.0144 |
+| 0.1053        | 102.56 | 4000  | 94.4738 | 0.0168 | 59.0288 | 0.3374          | 0.0552 |
+| 0.0999        | 115.38 | 4500  | 94.6291 | 0.0336 | 58.6283 | 0.3437          | 0.0624 |
+| 0.0941        | 128.21 | 5000  | 94.7896 | 0.0695 | 58.4149 | 0.3512          | 0.1271 |
+| 0.0904        | 141.03 | 5500  | 94.4101 | 0.0719 | 58.2518 | 0.3424          | 0.1439 |
+| 0.0833        | 153.85 | 6000  | 94.7141 | 0.0887 | 59.0312 | 0.3462          | 0.1775 |
+| 0.0772        | 166.67 | 6500  | 94.6758 | 0.0911 | 59.0767 | 0.3467          | 0.2062 |
+| 0.0722        | 179.49 | 7000  | 94.5698 | 0.1055 | 58.1415 | 0.3462          | 0.2398 |
+| 0.0669        | 192.31 | 7500  | 95.0365 | 0.1223 | 58.7794 | 0.3537          | 0.2782 |
+| 0.062         | 205.13 | 8000  | 94.8694 | 0.1247 | 58.211  | 0.3505          | 0.2686 |
+| 0.0576        | 217.95 | 8500  | 94.8168 | 0.1271 | 59.0791 | 0.3511          | 0.2926 |
+| 0.0539        | 230.77 | 9000  | 95.1935 | 0.1367 | 58.6787 | 0.3490          | 0.3046 |
+| 0.0502        | 243.59 | 9500  | 95.1882 | 0.1319 | 58.5228 | 0.3490          | 0.3141 |
+| 0.0473        | 256.41 | 10000 | 95.1198 | 0.1319 | 58.4245 | 0.3504          | 0.307  |
+| 0.045         | 269.23 | 10500 | 0.3505  | 95.047 | 0.1343  | 0.307           | 58.3213|
+| 0.0429        | 282.05 | 11000 | 0.3522  | 95.2397| 0.1391  | 0.3046          | 58.7242|
+| 0.0416        | 294.87 | 11500 | 0.3523  | 95.2821| 0.1415  | 0.3046          | 58.7746|
 
 
 ### Framework versions