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End of training

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README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1254
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  ## Model description
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@@ -33,7 +33,7 @@ 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: 2e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -49,20 +49,20 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.1516 | 0.56 | 500 | 0.1606 |
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- | 0.1076 | 1.12 | 1000 | 0.1337 |
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- | 0.1051 | 1.69 | 1500 | 0.1240 |
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- | 0.0711 | 2.25 | 2000 | 0.1221 |
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- | 0.0703 | 2.81 | 2500 | 0.1203 |
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- | 0.0532 | 3.37 | 3000 | 0.1207 |
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- | 0.0531 | 3.93 | 3500 | 0.1193 |
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- | 0.0368 | 4.49 | 4000 | 0.1217 |
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- | 0.024 | 5.06 | 4500 | 0.1219 |
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- | 0.0275 | 5.62 | 5000 | 0.1233 |
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- | 0.02 | 6.18 | 5500 | 0.1242 |
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- | 0.0217 | 6.74 | 6000 | 0.1245 |
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- | 0.0193 | 7.3 | 6500 | 0.1252 |
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- | 0.0199 | 7.87 | 7000 | 0.1254 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1273
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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: 1e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.2874 | 0.56 | 500 | 0.2242 |
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+ | 0.1208 | 1.12 | 1000 | 0.1447 |
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+ | 0.1207 | 1.69 | 1500 | 0.1350 |
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+ | 0.0928 | 2.25 | 2000 | 0.1312 |
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+ | 0.1008 | 2.81 | 2500 | 0.1278 |
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+ | 0.0769 | 3.37 | 3000 | 0.1272 |
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+ | 0.0799 | 3.93 | 3500 | 0.1259 |
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+ | 0.0689 | 4.49 | 4000 | 0.1266 |
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+ | 0.0593 | 5.06 | 4500 | 0.1263 |
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+ | 0.0534 | 5.62 | 5000 | 0.1270 |
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+ | 0.0497 | 6.18 | 5500 | 0.1268 |
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+ | 0.0483 | 6.74 | 6000 | 0.1268 |
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+ | 0.0453 | 7.3 | 6500 | 0.1274 |
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+ | 0.0486 | 7.87 | 7000 | 0.1273 |
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  ### Framework versions
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