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distilbert-base-uncased-distilled-clinc

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

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@@ -21,7 +21,7 @@ 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
@@ -31,8 +31,8 @@ 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: 0.3584
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- - Accuracy: 0.9455
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  ## Model description
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@@ -57,21 +57,22 @@ 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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- | 3.4679 | 1.0 | 318 | 2.5744 | 0.7461 |
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- | 1.9854 | 2.0 | 636 | 1.3150 | 0.8616 |
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- | 1.0196 | 3.0 | 954 | 0.7191 | 0.9087 |
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- | 0.5718 | 4.0 | 1272 | 0.4885 | 0.9348 |
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- | 0.3844 | 5.0 | 1590 | 0.4113 | 0.9429 |
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- | 0.3028 | 6.0 | 1908 | 0.3816 | 0.9432 |
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- | 0.2636 | 7.0 | 2226 | 0.3652 | 0.9461 |
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- | 0.2428 | 8.0 | 2544 | 0.3604 | 0.9452 |
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- | 0.2353 | 9.0 | 2862 | 0.3584 | 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: 0.9470967741935484
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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
 
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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: 0.3180
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+ - Accuracy: 0.9471
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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: 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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+ | 2.8197 | 1.0 | 318 | 2.0528 | 0.7435 |
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+ | 1.5825 | 2.0 | 636 | 1.0403 | 0.8684 |
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+ | 0.8215 | 3.0 | 954 | 0.5924 | 0.9110 |
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+ | 0.486 | 4.0 | 1272 | 0.4252 | 0.9345 |
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+ | 0.3488 | 5.0 | 1590 | 0.3693 | 0.9452 |
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+ | 0.2872 | 6.0 | 1908 | 0.3440 | 0.9452 |
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+ | 0.2564 | 7.0 | 2226 | 0.3297 | 0.9468 |
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+ | 0.2393 | 8.0 | 2544 | 0.3241 | 0.9465 |
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+ | 0.2317 | 9.0 | 2862 | 0.3208 | 0.9471 |
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+ | 0.2265 | 10.0 | 3180 | 0.3180 | 0.9471 |
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  ### Framework versions