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distilbert-base-uncased-finetuned-clinc

Text Classification
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distilbert
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text-embeddings-inference
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Training complete

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  1. README.md +14 -7
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -19,7 +19,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.7706451612903226
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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: 3.0672
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- - Accuracy: 0.7706
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  ## Model description
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@@ -55,15 +55,22 @@ 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: 3
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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 | 159 | 4.0708 | 0.62 |
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- | No log | 2.0 | 318 | 3.3162 | 0.7481 |
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- | No log | 3.0 | 477 | 3.0672 | 0.7706 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metric:
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  name: Accuracy
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  type: accuracy
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+ value: 0.9419354838709677
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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: 0.2929
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+ - Accuracy: 0.9419
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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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+ | No log | 1.0 | 159 | 1.7692 | 0.6606 |
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+ | No log | 2.0 | 318 | 1.1246 | 0.7997 |
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+ | No log | 3.0 | 477 | 0.7261 | 0.8681 |
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+ | 1.5283 | 4.0 | 636 | 0.5132 | 0.9106 |
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+ | 1.5283 | 5.0 | 795 | 0.4002 | 0.9232 |
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+ | 1.5283 | 6.0 | 954 | 0.3460 | 0.9342 |
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+ | 0.4714 | 7.0 | 1113 | 0.3171 | 0.9384 |
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+ | 0.4714 | 8.0 | 1272 | 0.3028 | 0.9410 |
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+ | 0.4714 | 9.0 | 1431 | 0.2947 | 0.9416 |
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+ | 0.2878 | 10.0 | 1590 | 0.2929 | 0.9419 |
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  ### Framework versions
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