Huseyin commited on
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Model save

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README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2222
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- - Precision: 0.9410
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- - Recall: 0.9416
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- - F1: 0.9413
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- - Accuracy: 0.9374
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  ## Model description
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@@ -44,21 +44,20 @@ More information needed
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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: 64
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- - eval_batch_size: 64
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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 | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 313 | 0.3063 | 0.9106 | 0.9115 | 0.9110 | 0.9073 |
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- | 0.5047 | 2.0 | 626 | 0.2395 | 0.9281 | 0.9357 | 0.9319 | 0.9284 |
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- | 0.5047 | 3.0 | 939 | 0.2174 | 0.9388 | 0.9426 | 0.9407 | 0.9372 |
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- | 0.2056 | 4.0 | 1252 | 0.2222 | 0.9410 | 0.9416 | 0.9413 | 0.9374 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2128
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+ - Precision: 0.9438
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+ - Recall: 0.9453
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+ - F1: 0.9446
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+ - Accuracy: 0.9412
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  ## Model description
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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: 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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.5739 | 1.0 | 625 | 0.2622 | 0.9206 | 0.9248 | 0.9227 | 0.9207 |
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+ | 0.2568 | 2.0 | 1250 | 0.2129 | 0.9382 | 0.9452 | 0.9417 | 0.9385 |
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+ | 0.1837 | 3.0 | 1875 | 0.2128 | 0.9438 | 0.9453 | 0.9446 | 0.9412 |
 
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  ### Framework versions
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