Vichentito commited on
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End of training

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README.md CHANGED
@@ -15,9 +15,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7196
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- - Bleu: 23.6683
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- - Gen Len: 45.6564
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  ## Model description
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@@ -36,69 +36,36 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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  - train_batch_size: 32
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  - eval_batch_size: 32
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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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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
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- | No log | 0.1071 | 100 | 0.6652 | 23.8215 | 46.146 |
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- | No log | 0.2141 | 200 | 0.6821 | 23.4518 | 45.8357 |
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- | No log | 0.3212 | 300 | 0.6870 | 23.1324 | 45.8827 |
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- | No log | 0.4283 | 400 | 0.7018 | 22.953 | 45.9213 |
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- | 0.983 | 0.5353 | 500 | 0.7049 | 22.98 | 45.8547 |
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- | 0.983 | 0.6424 | 600 | 0.7046 | 22.8865 | 45.9609 |
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- | 0.983 | 0.7495 | 700 | 0.7136 | 22.5721 | 45.478 |
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- | 0.983 | 0.8565 | 800 | 0.7137 | 22.5416 | 46.017 |
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- | 0.983 | 0.9636 | 900 | 0.7149 | 22.5314 | 45.7645 |
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- | 0.9989 | 1.0707 | 1000 | 0.7213 | 22.5012 | 45.9881 |
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- | 0.9989 | 1.1777 | 1100 | 0.7195 | 22.5104 | 45.6612 |
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- | 0.9989 | 1.2848 | 1200 | 0.7211 | 22.4268 | 46.085 |
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- | 0.9989 | 1.3919 | 1300 | 0.7220 | 22.5986 | 45.754 |
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- | 0.9989 | 1.4989 | 1400 | 0.7243 | 22.5969 | 46.077 |
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- | 0.9195 | 1.6060 | 1500 | 0.7300 | 22.6051 | 45.7915 |
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- | 0.9195 | 1.7131 | 1600 | 0.7255 | 22.563 | 45.8345 |
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- | 0.9195 | 1.8201 | 1700 | 0.7268 | 22.7627 | 45.7479 |
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- | 0.9195 | 1.9272 | 1800 | 0.7239 | 22.6867 | 45.9264 |
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- | 0.9195 | 2.0343 | 1900 | 0.7292 | 22.7507 | 45.6174 |
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- | 0.9069 | 2.1413 | 2000 | 0.7287 | 22.8822 | 45.7353 |
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- | 0.9069 | 2.2484 | 2100 | 0.7288 | 22.9287 | 45.7574 |
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- | 0.9069 | 2.3555 | 2200 | 0.7271 | 22.739 | 45.8887 |
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- | 0.9069 | 2.4625 | 2300 | 0.7295 | 22.7979 | 45.6375 |
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- | 0.9069 | 2.5696 | 2400 | 0.7255 | 22.8196 | 45.8767 |
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- | 0.8581 | 2.6767 | 2500 | 0.7285 | 22.9328 | 45.5503 |
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- | 0.8581 | 2.7837 | 2600 | 0.7272 | 22.8605 | 45.4845 |
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- | 0.8581 | 2.8908 | 2700 | 0.7266 | 22.7798 | 45.8115 |
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- | 0.8581 | 2.9979 | 2800 | 0.7263 | 22.8977 | 45.7137 |
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- | 0.8581 | 3.1049 | 2900 | 0.7278 | 23.1761 | 45.5648 |
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- | 0.8337 | 3.2120 | 3000 | 0.7253 | 23.1161 | 45.6975 |
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- | 0.8337 | 3.3191 | 3100 | 0.7254 | 23.2943 | 45.8444 |
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- | 0.8337 | 3.4261 | 3200 | 0.7269 | 23.3569 | 45.5949 |
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- | 0.8337 | 3.5332 | 3300 | 0.7249 | 23.3935 | 45.7649 |
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- | 0.8337 | 3.6403 | 3400 | 0.7245 | 23.3007 | 45.7151 |
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- | 0.7951 | 3.7473 | 3500 | 0.7256 | 23.2827 | 45.5649 |
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- | 0.7951 | 3.8544 | 3600 | 0.7224 | 23.4464 | 45.7041 |
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- | 0.7951 | 3.9615 | 3700 | 0.7209 | 23.4635 | 45.6198 |
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- | 0.7951 | 4.0685 | 3800 | 0.7261 | 23.4885 | 45.6302 |
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- | 0.7951 | 4.1756 | 3900 | 0.7226 | 23.5112 | 45.6264 |
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- | 0.769 | 4.2827 | 4000 | 0.7226 | 23.4213 | 45.6869 |
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- | 0.769 | 4.3897 | 4100 | 0.7219 | 23.5038 | 45.4214 |
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- | 0.769 | 4.4968 | 4200 | 0.7211 | 23.5617 | 45.6644 |
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- | 0.769 | 4.6039 | 4300 | 0.7201 | 23.5387 | 45.742 |
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- | 0.769 | 4.7109 | 4400 | 0.7199 | 23.5526 | 45.6596 |
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- | 0.7513 | 4.8180 | 4500 | 0.7193 | 23.6482 | 45.6834 |
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- | 0.7513 | 4.9251 | 4600 | 0.7196 | 23.6683 | 45.6564 |
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  ### Framework versions
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- - Transformers 4.40.1
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- - Pytorch 2.2.1+cu121
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- - Datasets 2.19.0
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  - Tokenizers 0.19.1
 
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6835
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+ - Bleu: 25.7459
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+ - Gen Len: 45.7999
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0005
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  - train_batch_size: 32
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  - eval_batch_size: 32
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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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+ - num_epochs: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
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+ | No log | 0.3027 | 300 | 0.6651 | 24.827 | 46.2006 |
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+ | 0.9651 | 0.6054 | 600 | 0.6967 | 24.0607 | 45.3494 |
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+ | 0.9651 | 0.9082 | 900 | 0.7045 | 23.7928 | 46.1327 |
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+ | 1.001 | 1.2109 | 1200 | 0.7084 | 23.9299 | 46.4082 |
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+ | 0.8741 | 1.5136 | 1500 | 0.7156 | 23.9047 | 45.8685 |
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+ | 0.8741 | 1.8163 | 1800 | 0.7121 | 23.9386 | 45.7796 |
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+ | 0.8763 | 2.1191 | 2100 | 0.7083 | 24.5377 | 45.8846 |
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+ | 0.8763 | 2.4218 | 2400 | 0.7032 | 24.6723 | 46.1827 |
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+ | 0.7689 | 2.7245 | 2700 | 0.6988 | 24.7631 | 45.8793 |
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+ | 0.7599 | 3.0272 | 3000 | 0.6961 | 25.2701 | 45.7947 |
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+ | 0.7599 | 3.3300 | 3300 | 0.6935 | 25.4704 | 45.7461 |
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+ | 0.6782 | 3.6327 | 3600 | 0.6861 | 25.7835 | 45.9797 |
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+ | 0.6782 | 3.9354 | 3900 | 0.6835 | 25.7459 | 45.7999 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
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  - Tokenizers 0.19.1
generation_config.json CHANGED
@@ -2,5 +2,5 @@
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  }
 
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