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distilbert-base-uncased-finetuned-osdg

Text Classification Transformers PyTorch TensorBoard distilbert generated_from_trainer Inference Endpoints
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: distilbert-base-uncased-finetuned-osdg
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  results: []
@@ -14,8 +16,9 @@ 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: 0.5699
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- - Acc: 0.8533
 
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  ## Model description
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@@ -34,25 +37,38 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 6e-06
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- - train_batch_size: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 7
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Acc |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.8138 | 1.0 | 509 | 0.7623 | 0.8157 |
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- | 0.6972 | 2.0 | 1018 | 0.6599 | 0.8312 |
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- | 0.5908 | 3.0 | 1527 | 0.6084 | 0.8428 |
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- | 0.5674 | 4.0 | 2036 | 0.5922 | 0.8467 |
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- | 0.5176 | 5.0 | 2545 | 0.5807 | 0.8533 |
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- | 0.4818 | 6.0 | 3054 | 0.5695 | 0.8556 |
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- | 0.4631 | 7.0 | 3563 | 0.5699 | 0.8533 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: distilbert-base-uncased-finetuned-osdg
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  results: []
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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: 1.8193
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+ - F1 Score: 0.7962
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+ - Accuracy: 0.8434
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 20
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Score | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
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+ | 0.3769 | 1.0 | 1017 | 0.8258 | 0.7729 | 0.8257 |
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+ | 0.2759 | 2.0 | 2034 | 0.8364 | 0.7773 | 0.8262 |
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+ | 0.1412 | 3.0 | 3051 | 1.0203 | 0.7833 | 0.8379 |
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+ | 0.1423 | 4.0 | 4068 | 1.1603 | 0.7683 | 0.8224 |
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+ | 0.0939 | 5.0 | 5085 | 1.3029 | 0.7843 | 0.8329 |
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+ | 0.0757 | 6.0 | 6102 | 1.3562 | 0.7931 | 0.8379 |
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+ | 0.0801 | 7.0 | 7119 | 1.2925 | 0.7840 | 0.8395 |
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+ | 0.0311 | 8.0 | 8136 | 1.4632 | 0.7750 | 0.8318 |
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+ | 0.0263 | 9.0 | 9153 | 1.5760 | 0.7843 | 0.8312 |
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+ | 0.0196 | 10.0 | 10170 | 1.5689 | 0.7890 | 0.8417 |
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+ | 0.0313 | 11.0 | 11187 | 1.6034 | 0.7909 | 0.8417 |
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+ | 0.0007 | 12.0 | 12204 | 1.6725 | 0.7889 | 0.8406 |
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+ | 0.0081 | 13.0 | 13221 | 1.6463 | 0.7911 | 0.8395 |
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+ | 0.0061 | 14.0 | 14238 | 1.7730 | 0.7861 | 0.8345 |
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+ | 0.003 | 15.0 | 15255 | 1.8001 | 0.7847 | 0.8379 |
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+ | 0.0002 | 16.0 | 16272 | 1.7328 | 0.7912 | 0.8434 |
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+ | 0.0 | 17.0 | 17289 | 1.7914 | 0.8011 | 0.8489 |
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+ | 0.0009 | 18.0 | 18306 | 1.7772 | 0.7958 | 0.8456 |
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+ | 0.0 | 19.0 | 19323 | 1.8028 | 0.7958 | 0.8434 |
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+ | 0.0 | 20.0 | 20340 | 1.8193 | 0.7962 | 0.8434 |
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  ### Framework versions