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robkayinto
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distilbert-base-uncased-distilled-clinc

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

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  1. README.md +13 -14
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@@ -19,7 +19,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9470967741935484
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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
@@ -29,8 +29,8 @@ 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: 0.3001
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- - Accuracy: 0.9471
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  ## Model description
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@@ -55,22 +55,21 @@ 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: 10
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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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- | 2.5578 | 1.0 | 318 | 1.8421 | 0.7381 |
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- | 1.4252 | 2.0 | 636 | 0.9391 | 0.8574 |
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- | 0.7512 | 3.0 | 954 | 0.5429 | 0.9145 |
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- | 0.4542 | 4.0 | 1272 | 0.4011 | 0.9345 |
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- | 0.3288 | 5.0 | 1590 | 0.3454 | 0.9416 |
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- | 0.2758 | 6.0 | 1908 | 0.3244 | 0.9435 |
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- | 0.2479 | 7.0 | 2226 | 0.3113 | 0.9458 |
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- | 0.2344 | 8.0 | 2544 | 0.3045 | 0.9458 |
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- | 0.2266 | 9.0 | 2862 | 0.3013 | 0.9468 |
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- | 0.2226 | 10.0 | 3180 | 0.3001 | 0.9471 |
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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: 0.9458064516129032
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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: 0.3029
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+ - Accuracy: 0.9458
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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: 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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+ | 2.9021 | 1.0 | 318 | 2.1478 | 0.7506 |
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+ | 1.6715 | 2.0 | 636 | 1.1280 | 0.8565 |
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+ | 0.8939 | 3.0 | 954 | 0.6438 | 0.9148 |
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+ | 0.5278 | 4.0 | 1272 | 0.4523 | 0.93 |
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+ | 0.36 | 5.0 | 1590 | 0.3688 | 0.94 |
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+ | 0.2827 | 6.0 | 1908 | 0.3355 | 0.9429 |
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+ | 0.2413 | 7.0 | 2226 | 0.3156 | 0.9458 |
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+ | 0.2214 | 8.0 | 2544 | 0.3069 | 0.9455 |
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+ | 0.2116 | 9.0 | 2862 | 0.3029 | 0.9458 |
 
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  ### Framework versions