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Ridealist
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distilbert-base-uncased-distilled-clinc

Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files
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Training complete

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Files changed (3) hide show
  1. README.md +14 -14
  2. pytorch_model.bin +2 -2
  3. training_args.bin +2 -2
README.md CHANGED
@@ -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: 0.03225806451612903
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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: nan
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- - Accuracy: 0.0323
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  ## Model description
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@@ -64,21 +64,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.0 | 1.0 | 318 | nan | 0.0065 |
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- | 0.0 | 2.0 | 636 | nan | 0.0323 |
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- | 0.0 | 3.0 | 954 | nan | 0.0323 |
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- | 0.0 | 4.0 | 1272 | nan | 0.0323 |
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- | 0.0 | 5.0 | 1590 | nan | 0.0323 |
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- | 0.0 | 6.0 | 1908 | nan | 0.0323 |
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- | 0.0 | 7.0 | 2226 | nan | 0.0323 |
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- | 0.0 | 8.0 | 2544 | nan | 0.0323 |
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- | 0.0 | 9.0 | 2862 | nan | 0.0323 |
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- | 0.0 | 10.0 | 3180 | nan | 0.0323 |
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  ### Framework versions
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  - Transformers 4.34.0
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- - Pytorch 2.1.0+cu121
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  - Datasets 2.4.0
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  - Tokenizers 0.14.1
 
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  metrics:
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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: 0.1002
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+ - Accuracy: 0.9419
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.9029 | 1.0 | 318 | 0.5766 | 0.7216 |
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+ | 0.4487 | 2.0 | 636 | 0.2855 | 0.8755 |
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+ | 0.2535 | 3.0 | 954 | 0.1780 | 0.9287 |
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+ | 0.1767 | 4.0 | 1272 | 0.1384 | 0.9319 |
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+ | 0.142 | 5.0 | 1590 | 0.1212 | 0.9339 |
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+ | 0.1245 | 6.0 | 1908 | 0.1115 | 0.9397 |
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+ | 0.1143 | 7.0 | 2226 | 0.1058 | 0.9416 |
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+ | 0.108 | 8.0 | 2544 | 0.1025 | 0.9423 |
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+ | 0.1039 | 9.0 | 2862 | 0.1009 | 0.9423 |
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+ | 0.102 | 10.0 | 3180 | 0.1002 | 0.9419 |
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  ### Framework versions
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  - Transformers 4.34.0
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+ - Pytorch 1.12.1+cu116
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  - Datasets 2.4.0
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  - Tokenizers 0.14.1
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