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distilbert-base-uncased_fold_1_binary

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
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update model card README.md

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@@ -16,8 +16,8 @@ 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: 1.1222
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- - F1: 0.7596
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  ## Model description
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@@ -48,31 +48,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 1.0 | 288 | 0.4130 | 0.7517 |
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- | 0.3938 | 2.0 | 576 | 0.4260 | 0.7330 |
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- | 0.3938 | 3.0 | 864 | 0.5000 | 0.7488 |
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- | 0.19 | 4.0 | 1152 | 0.7415 | 0.7487 |
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- | 0.19 | 5.0 | 1440 | 0.8994 | 0.7397 |
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- | 0.0903 | 6.0 | 1728 | 0.9835 | 0.7386 |
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- | 0.0392 | 7.0 | 2016 | 1.1222 | 0.7596 |
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- | 0.0392 | 8.0 | 2304 | 1.2018 | 0.7314 |
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- | 0.0234 | 9.0 | 2592 | 1.2691 | 0.7330 |
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- | 0.0234 | 10.0 | 2880 | 1.2972 | 0.7496 |
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- | 0.0182 | 11.0 | 3168 | 1.4606 | 0.7492 |
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- | 0.0182 | 12.0 | 3456 | 1.4766 | 0.7361 |
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- | 0.006 | 13.0 | 3744 | 1.4888 | 0.7500 |
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- | 0.0057 | 14.0 | 4032 | 1.5684 | 0.7298 |
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- | 0.0057 | 15.0 | 4320 | 1.5354 | 0.7509 |
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- | 0.0058 | 16.0 | 4608 | 1.7733 | 0.7436 |
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- | 0.0058 | 17.0 | 4896 | 1.5695 | 0.7512 |
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- | 0.0089 | 18.0 | 5184 | 1.6593 | 0.7430 |
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- | 0.0089 | 19.0 | 5472 | 1.7092 | 0.7444 |
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- | 0.0048 | 20.0 | 5760 | 1.7206 | 0.7374 |
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- | 0.002 | 21.0 | 6048 | 1.7440 | 0.7343 |
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- | 0.002 | 22.0 | 6336 | 1.7582 | 0.7347 |
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- | 0.0006 | 23.0 | 6624 | 1.7294 | 0.7472 |
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- | 0.0006 | 24.0 | 6912 | 1.7454 | 0.7365 |
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- | 0.0001 | 25.0 | 7200 | 1.7395 | 0.7429 |
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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: 1.5992
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+ - F1: 0.7687
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 288 | 0.3960 | 0.7467 |
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+ | 0.3988 | 2.0 | 576 | 0.3947 | 0.7487 |
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+ | 0.3988 | 3.0 | 864 | 0.4511 | 0.7662 |
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+ | 0.1853 | 4.0 | 1152 | 0.7226 | 0.7285 |
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+ | 0.1853 | 5.0 | 1440 | 0.9398 | 0.7334 |
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+ | 0.0827 | 6.0 | 1728 | 1.0547 | 0.7427 |
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+ | 0.0287 | 7.0 | 2016 | 1.1602 | 0.7563 |
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+ | 0.0287 | 8.0 | 2304 | 1.3332 | 0.7171 |
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+ | 0.0219 | 9.0 | 2592 | 1.3429 | 0.7420 |
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+ | 0.0219 | 10.0 | 2880 | 1.2603 | 0.7648 |
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+ | 0.0139 | 11.0 | 3168 | 1.4126 | 0.7569 |
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+ | 0.0139 | 12.0 | 3456 | 1.3195 | 0.7483 |
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+ | 0.0115 | 13.0 | 3744 | 1.4356 | 0.7491 |
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+ | 0.0035 | 14.0 | 4032 | 1.5693 | 0.7636 |
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+ | 0.0035 | 15.0 | 4320 | 1.4071 | 0.7662 |
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+ | 0.0071 | 16.0 | 4608 | 1.4561 | 0.7579 |
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+ | 0.0071 | 17.0 | 4896 | 1.5405 | 0.7634 |
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+ | 0.0041 | 18.0 | 5184 | 1.5862 | 0.7589 |
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+ | 0.0041 | 19.0 | 5472 | 1.6782 | 0.76 |
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+ | 0.0024 | 20.0 | 5760 | 1.5699 | 0.7677 |
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+ | 0.0006 | 21.0 | 6048 | 1.5991 | 0.7467 |
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+ | 0.0006 | 22.0 | 6336 | 1.6205 | 0.7682 |
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+ | 0.0003 | 23.0 | 6624 | 1.6334 | 0.7643 |
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+ | 0.0003 | 24.0 | 6912 | 1.5992 | 0.7687 |
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+ | 0.0011 | 25.0 | 7200 | 1.6053 | 0.7624 |
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  ### Framework versions