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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 +20 -20
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,16 +14,16 @@ 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: 0.1546
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- - Train Mae: 0.2782
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- - Train Mse: 0.1307
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- - Train Accuracy: 0.7385
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- - Train R2-score: 0.7406
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- - Validation Loss: 0.1848
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- - Validation Mae: 0.3685
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- - Validation Mse: 0.1836
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- - Validation Accuracy: 0.5135
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- - Validation R2-score: 0.8571
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  - Epoch: 9
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  ## Model description
@@ -50,16 +50,16 @@ The following hyperparameters were used during training:
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  | Train Loss | Train Mae | Train Mse | Train Accuracy | Train R2-score | Validation Loss | Validation Mae | Validation Mse | Validation Accuracy | Validation R2-score | Epoch |
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  |:----------:|:---------:|:---------:|:--------------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-------------------:|:-----:|
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- | 1.0436 | 0.3757 | 0.2130 | 0.6769 | 0.5094 | 0.1461 | 0.3402 | 0.1443 | 0.9459 | 0.8772 | 0 |
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- | 0.2542 | 0.3126 | 0.1525 | 0.7154 | 0.6927 | 0.3952 | 0.5822 | 0.3950 | 0.3243 | 0.6797 | 1 |
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- | 0.1743 | 0.3049 | 0.1439 | 0.7231 | 0.6964 | 0.0748 | 0.2426 | 0.0722 | 0.9459 | 0.9034 | 2 |
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- | 0.4325 | 0.3154 | 0.1510 | 0.7077 | 0.6992 | 0.1663 | 0.3678 | 0.1641 | 0.8108 | 0.8491 | 3 |
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- | 0.2468 | 0.3069 | 0.1444 | 0.7385 | 0.3708 | 0.2735 | 0.4726 | 0.2728 | 0.3243 | 0.7953 | 4 |
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- | 0.3008 | 0.3204 | 0.1563 | 0.7308 | 0.7149 | 0.1543 | 0.3460 | 0.1527 | 0.9459 | 0.8730 | 5 |
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- | 0.1985 | 0.2822 | 0.1335 | 0.7000 | 0.7389 | 0.2090 | 0.3995 | 0.2079 | 0.3243 | 0.8411 | 6 |
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- | 0.2017 | 0.3021 | 0.1472 | 0.7231 | 0.7224 | 0.1305 | 0.3280 | 0.1286 | 0.9459 | 0.8820 | 7 |
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- | 0.2121 | 0.2961 | 0.1375 | 0.7308 | 0.7781 | 0.1706 | 0.3553 | 0.1692 | 0.9730 | 0.8655 | 8 |
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- | 0.1546 | 0.2782 | 0.1307 | 0.7385 | 0.7406 | 0.1848 | 0.3685 | 0.1836 | 0.5135 | 0.8571 | 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: 0.2128
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+ - Train Mae: 0.2623
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+ - Train Mse: 0.1098
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+ - Train Accuracy: 0.8615
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+ - Train R2-score: 0.8081
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+ - Validation Loss: 0.1657
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+ - Validation Mae: 0.3472
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+ - Validation Mse: 0.1644
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+ - Validation Accuracy: 0.7027
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+ - Validation R2-score: 0.8599
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  - Epoch: 9
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  ## Model description
 
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  | Train Loss | Train Mae | Train Mse | Train Accuracy | Train R2-score | Validation Loss | Validation Mae | Validation Mse | Validation Accuracy | Validation R2-score | Epoch |
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  |:----------:|:---------:|:---------:|:--------------:|:--------------:|:---------------:|:--------------:|:--------------:|:-------------------:|:-------------------:|:-----:|
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+ | 0.6256 | 0.3353 | 0.1579 | 0.7615 | 0.4024 | 0.2916 | 0.4907 | 0.2909 | 0.3243 | 0.7810 | 0 |
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+ | 0.3639 | 0.3290 | 0.1605 | 0.7077 | 0.3874 | 0.3009 | 0.5004 | 0.3003 | 0.3243 | 0.7733 | 1 |
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+ | 0.1835 | 0.2940 | 0.1415 | 0.6615 | 0.7274 | 0.2086 | 0.3992 | 0.2075 | 0.3243 | 0.8417 | 2 |
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+ | 0.1707 | 0.2955 | 0.1462 | 0.5846 | 0.7594 | 0.1872 | 0.3705 | 0.1859 | 0.3243 | 0.8547 | 3 |
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+ | 0.1628 | 0.2740 | 0.1251 | 0.8077 | 0.7588 | 0.1867 | 0.3707 | 0.1854 | 0.4595 | 0.8547 | 4 |
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+ | 0.1541 | 0.2695 | 0.1221 | 0.7769 | 0.7405 | 0.1851 | 0.3696 | 0.1839 | 0.5946 | 0.8549 | 5 |
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+ | 0.2239 | 0.2983 | 0.1388 | 0.7154 | 0.7428 | 0.2561 | 0.4564 | 0.2552 | 0.3243 | 0.7987 | 6 |
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+ | 0.1998 | 0.2815 | 0.1295 | 0.7538 | 0.7537 | 0.1979 | 0.3872 | 0.1968 | 0.3514 | 0.8473 | 7 |
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+ | 0.1682 | 0.2743 | 0.1260 | 0.7692 | 0.7532 | 0.1515 | 0.3350 | 0.1500 | 0.9730 | 0.8691 | 8 |
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+ | 0.2128 | 0.2623 | 0.1098 | 0.8615 | 0.8081 | 0.1657 | 0.3472 | 0.1644 | 0.7027 | 0.8599 | 9 |
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  ### Framework versions
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