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eskayML
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bert_combined_top

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
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eskayML/bert_combined_top_2

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  1. README.md +12 -12
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ 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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4672
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- - Accuracy: 0.7692
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  ## Model description
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@@ -50,16 +50,16 @@ 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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- | 0.9678 | 1.0 | 624 | 0.8407 | 0.6154 |
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- | 0.8021 | 2.0 | 1248 | 0.9407 | 0.6955 |
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- | 0.646 | 3.0 | 1872 | 1.0495 | 0.7372 |
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- | 0.503 | 4.0 | 2496 | 1.2148 | 0.7436 |
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- | 0.2171 | 5.0 | 3120 | 1.2175 | 0.7564 |
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- | 0.1784 | 6.0 | 3744 | 1.2755 | 0.7724 |
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- | 0.1038 | 7.0 | 4368 | 1.4106 | 0.7660 |
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- | 0.1458 | 8.0 | 4992 | 1.3917 | 0.7949 |
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- | 0.0707 | 9.0 | 5616 | 1.4302 | 0.7756 |
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- | 0.0716 | 10.0 | 6240 | 1.4672 | 0.7692 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0320
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+ - Accuracy: 0.9872
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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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+ | 0.9945 | 1.0 | 780 | 0.7471 | 0.7179 |
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+ | 0.7659 | 2.0 | 1560 | 0.5219 | 0.8269 |
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+ | 0.5512 | 3.0 | 2340 | 0.3141 | 0.9199 |
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+ | 0.372 | 4.0 | 3120 | 0.2176 | 0.9519 |
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+ | 0.2519 | 5.0 | 3900 | 0.1440 | 0.9679 |
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+ | 0.172 | 6.0 | 4680 | 0.1142 | 0.9776 |
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+ | 0.1873 | 7.0 | 5460 | 0.0943 | 0.9808 |
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+ | 0.0807 | 8.0 | 6240 | 0.0449 | 0.9904 |
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+ | 0.1075 | 9.0 | 7020 | 0.0432 | 0.9904 |
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+ | 0.0479 | 10.0 | 7800 | 0.0320 | 0.9872 |
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  ### Framework versions
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