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distilbert-base-uncased-distilled-clinc

Text Classification
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PyTorch
distilbert
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Eval Results
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update model card README.md

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@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9454838709677419
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2567
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- - Accuracy: 0.9455
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  ## Model description
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@@ -58,21 +58,19 @@ The following hyperparameters were used during training:
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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: 9
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 318 | 2.0110 | 0.7358 |
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- | 2.3641 | 2.0 | 636 | 1.0585 | 0.8655 |
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- | 2.3641 | 3.0 | 954 | 0.6025 | 0.9171 |
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- | 0.9391 | 4.0 | 1272 | 0.4140 | 0.9365 |
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- | 0.4122 | 5.0 | 1590 | 0.3299 | 0.9419 |
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- | 0.4122 | 6.0 | 1908 | 0.2880 | 0.9423 |
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- | 0.2477 | 7.0 | 2226 | 0.2699 | 0.9432 |
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- | 0.1912 | 8.0 | 2544 | 0.2593 | 0.9448 |
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- | 0.1912 | 9.0 | 2862 | 0.2567 | 0.9455 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.94
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2392
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+ - Accuracy: 0.94
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  ## Model description
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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: 7
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 318 | 1.2861 | 0.7445 |
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+ | 1.556 | 2.0 | 636 | 0.7019 | 0.8677 |
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+ | 1.556 | 3.0 | 954 | 0.4289 | 0.9190 |
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+ | 0.6453 | 4.0 | 1272 | 0.3133 | 0.9313 |
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+ | 0.3314 | 5.0 | 1590 | 0.2654 | 0.9348 |
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+ | 0.3314 | 6.0 | 1908 | 0.2448 | 0.9397 |
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+ | 0.2393 | 7.0 | 2226 | 0.2392 | 0.94 |
 
 
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  ### Framework versions