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BERT2BERT_finetuned

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update model card README.md

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