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distilbert-qa-checkpoint-v2

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update model card README.md

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@@ -14,7 +14,7 @@ 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: 0.4324
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  ## Model description
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@@ -39,22 +39,32 @@ 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 |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 287 | 0.3914 |
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- | 0.7085 | 2.0 | 574 | 0.3344 |
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- | 0.7085 | 3.0 | 861 | 0.3401 |
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- | 0.2515 | 4.0 | 1148 | 0.3554 |
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- | 0.2515 | 5.0 | 1435 | 0.3821 |
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- | 0.1556 | 6.0 | 1722 | 0.4120 |
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- | 0.102 | 7.0 | 2009 | 0.3988 |
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- | 0.102 | 8.0 | 2296 | 0.4214 |
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- | 0.0737 | 9.0 | 2583 | 0.4179 |
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- | 0.0737 | 10.0 | 2870 | 0.4324 |
 
 
 
 
 
 
 
 
 
 
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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: 0.3141
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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: 20
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 0.6564 | 1.0 | 658 | 0.3612 |
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+ | 0.3397 | 2.0 | 1316 | 0.3361 |
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+ | 0.2885 | 3.0 | 1974 | 0.3515 |
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+ | 0.2407 | 4.0 | 2632 | 0.3672 |
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+ | 0.2213 | 5.0 | 3290 | 0.3718 |
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+ | 0.2197 | 6.0 | 3948 | 0.3967 |
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+ | 0.1986 | 7.0 | 4606 | 0.4115 |
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+ | 0.1932 | 8.0 | 5264 | 0.4152 |
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+ | 0.19 | 9.0 | 5922 | 0.4208 |
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+ | 0.1844 | 10.0 | 6580 | 0.4472 |
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+ | 0.1824 | 11.0 | 7238 | 0.4466 |
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+ | 0.1812 | 12.0 | 7896 | 0.2695 |
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+ | 0.0078 | 13.0 | 8554 | 0.2824 |
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+ | 0.0073 | 14.0 | 9212 | 0.2793 |
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+ | 0.0048 | 15.0 | 9870 | 0.3107 |
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+ | 0.0033 | 16.0 | 10528 | 0.3074 |
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+ | 0.0022 | 17.0 | 11186 | 0.3073 |
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+ | 0.0038 | 18.0 | 11844 | 0.3147 |
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+ | 0.0013 | 19.0 | 12502 | 0.3160 |
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+ | 0.0008 | 20.0 | 13160 | 0.3141 |
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  ### Framework versions