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Regression_bert_1

Text Classification
Transformers
TensorFlow
distilbert
generated_from_keras_callback
Inference Endpoints
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Upload TFDistilBertForSequenceClassification

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  1. README.md +18 -18
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,14 +14,14 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.1782
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- - Train Mae: 0.2820
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- - Train Mse: 0.1314
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- - Train R2-score: 0.7570
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- - Validation Loss: 0.1590
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- - Validation Mae: 0.3493
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- - Validation Mse: 0.1575
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- - Validation R2-score: 0.8711
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  - Epoch: 9
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  ## Model description
@@ -48,16 +48,16 @@ The following hyperparameters were used during training:
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  | Train Loss | Train Mae | Train Mse | Train R2-score | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Epoch |
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  |:----------:|:---------:|:---------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-----:|
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- | 0.2900 | 0.2663 | 0.1055 | 0.4630 | 0.1897 | 0.3738 | 0.1885 | 0.8539 | 0 |
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- | 0.1922 | 0.3084 | 0.1536 | 0.4341 | 0.2302 | 0.4254 | 0.2293 | 0.8277 | 1 |
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- | 0.3804 | 0.3059 | 0.1401 | 0.2020 | 0.1218 | 0.3206 | 0.1197 | 0.8852 | 2 |
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- | 0.2828 | 0.3079 | 0.1426 | 0.7285 | 0.1612 | 0.3507 | 0.1597 | 0.8700 | 3 |
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- | 0.1689 | 0.2803 | 0.1282 | 0.7133 | 0.2451 | 0.4425 | 0.2443 | 0.8173 | 4 |
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- | 0.1746 | 0.2955 | 0.1469 | 0.7545 | 0.2007 | 0.3887 | 0.1995 | 0.8472 | 5 |
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- | 0.1674 | 0.2840 | 0.1372 | -4.4884 | 0.1849 | 0.3671 | 0.1836 | 0.8569 | 6 |
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- | 0.1691 | 0.2853 | 0.1351 | 0.7348 | 0.1985 | 0.3857 | 0.1973 | 0.8486 | 7 |
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- | 0.1615 | 0.2909 | 0.1414 | 0.7511 | 0.1867 | 0.3696 | 0.1854 | 0.8558 | 8 |
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- | 0.1782 | 0.2820 | 0.1314 | 0.7570 | 0.1590 | 0.3493 | 0.1575 | 0.8711 | 9 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.1783
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+ - Train Mae: 0.2454
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+ - Train Mse: 0.1031
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+ - Train R2-score: 0.4142
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+ - Validation Loss: 0.0857
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+ - Validation Mae: 0.2032
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+ - Validation Mse: 0.0821
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+ - Validation R2-score: 0.8682
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  - Epoch: 9
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  ## Model description
 
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  | Train Loss | Train Mae | Train Mse | Train R2-score | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Epoch |
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  |:----------:|:---------:|:---------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-----:|
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+ | 0.8164 | 0.3447 | 0.1992 | 0.5384 | 0.1862 | 0.3708 | 0.1849 | 0.8553 | 0 |
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+ | 0.2232 | 0.2734 | 0.1179 | 0.6082 | 0.2813 | 0.4837 | 0.2806 | 0.7862 | 1 |
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+ | 0.2817 | 0.3236 | 0.1602 | 0.6175 | 0.1569 | 0.3480 | 0.1553 | 0.8720 | 2 |
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+ | 0.2010 | 0.2856 | 0.1359 | 0.7224 | 0.2089 | 0.3973 | 0.2077 | 0.8394 | 3 |
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+ | 0.1825 | 0.2874 | 0.1365 | 0.7419 | 0.1608 | 0.3494 | 0.1593 | 0.8698 | 4 |
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+ | 0.1773 | 0.2616 | 0.1055 | 0.7859 | 0.2236 | 0.4185 | 0.2226 | 0.8301 | 5 |
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+ | 0.2332 | 0.3060 | 0.1529 | 0.7090 | 0.1610 | 0.3488 | 0.1595 | 0.8684 | 6 |
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+ | 0.1951 | 0.2734 | 0.1223 | 0.7305 | 0.1565 | 0.3434 | 0.1550 | 0.8695 | 7 |
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+ | 0.1249 | 0.2412 | 0.1018 | 0.8066 | 0.0774 | 0.2095 | 0.0756 | 0.8936 | 8 |
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+ | 0.1783 | 0.2454 | 0.1031 | 0.4142 | 0.0857 | 0.2032 | 0.0821 | 0.8682 | 9 |
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  ### Framework versions
tf_model.h5 CHANGED
@@ -1,3 +1,3 @@
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