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ankush-003
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nosql-identifier-bert

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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update model card README.md

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  1. README.md +18 -13
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@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3451
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- - Accuracy: 0.875
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  ## Model description
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@@ -43,22 +43,27 @@ The following hyperparameters were used during training:
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 40 | 0.5068 | 0.9 |
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- | No log | 2.0 | 80 | 0.2525 | 0.925 |
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- | No log | 3.0 | 120 | 0.2196 | 0.95 |
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- | No log | 4.0 | 160 | 0.2386 | 0.925 |
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- | No log | 5.0 | 200 | 0.3151 | 0.9 |
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- | No log | 6.0 | 240 | 0.2646 | 0.875 |
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- | No log | 7.0 | 280 | 0.4246 | 0.825 |
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- | No log | 8.0 | 320 | 0.3511 | 0.875 |
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- | No log | 9.0 | 360 | 0.3062 | 0.9 |
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- | No log | 10.0 | 400 | 0.3451 | 0.875 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1533
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+ - Accuracy: 0.95
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  ## Model description
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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: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 40 | 0.5050 | 0.75 |
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+ | No log | 2.0 | 80 | 0.2764 | 0.9 |
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+ | No log | 3.0 | 120 | 0.1961 | 0.925 |
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+ | No log | 4.0 | 160 | 0.2393 | 0.925 |
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+ | No log | 5.0 | 200 | 0.1336 | 0.975 |
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+ | No log | 6.0 | 240 | 0.3407 | 0.8 |
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+ | No log | 7.0 | 280 | 0.3620 | 0.85 |
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+ | No log | 8.0 | 320 | 0.1338 | 0.95 |
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+ | No log | 9.0 | 360 | 0.1569 | 0.925 |
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+ | No log | 10.0 | 400 | 0.1155 | 0.95 |
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+ | No log | 11.0 | 440 | 0.2435 | 0.9 |
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+ | No log | 12.0 | 480 | 0.2488 | 0.925 |
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+ | 0.2805 | 13.0 | 520 | 0.2693 | 0.925 |
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+ | 0.2805 | 14.0 | 560 | 0.1427 | 0.975 |
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+ | 0.2805 | 15.0 | 600 | 0.1533 | 0.95 |
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  ### Framework versions