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distilbert-base-uncased-finetuned-intro-verizon

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update model card README.md

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@@ -17,7 +17,7 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3754
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  - Accuracy: 1.0
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  - F1: 1.0
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@@ -44,22 +44,32 @@ 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 | Accuracy | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 1.0941 | 1.0 | 3 | 0.9683 | 1.0 | 1.0 |
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- | 0.8881 | 2.0 | 6 | 0.8225 | 0.9524 | 0.9527 |
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- | 0.8007 | 3.0 | 9 | 0.7050 | 1.0 | 1.0 |
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- | 0.643 | 4.0 | 12 | 0.6111 | 1.0 | 1.0 |
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- | 0.5962 | 5.0 | 15 | 0.5348 | 1.0 | 1.0 |
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- | 0.4978 | 6.0 | 18 | 0.4752 | 1.0 | 1.0 |
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- | 0.4832 | 7.0 | 21 | 0.4315 | 1.0 | 1.0 |
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- | 0.4416 | 8.0 | 24 | 0.4012 | 1.0 | 1.0 |
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- | 0.4232 | 9.0 | 27 | 0.3826 | 1.0 | 1.0 |
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- | 0.3952 | 10.0 | 30 | 0.3754 | 1.0 | 1.0 |
 
 
 
 
 
 
 
 
 
 
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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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+ - Loss: 0.0400
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  - Accuracy: 1.0
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  - F1: 1.0
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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 | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
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+ | 0.3753 | 1.0 | 3 | 0.2877 | 1.0 | 1.0 |
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+ | 0.278 | 2.0 | 6 | 0.2253 | 1.0 | 1.0 |
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+ | 0.2366 | 3.0 | 9 | 0.1788 | 1.0 | 1.0 |
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+ | 0.1721 | 4.0 | 12 | 0.1433 | 1.0 | 1.0 |
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+ | 0.1531 | 5.0 | 15 | 0.1173 | 1.0 | 1.0 |
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+ | 0.117 | 6.0 | 18 | 0.0980 | 1.0 | 1.0 |
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+ | 0.108 | 7.0 | 21 | 0.0841 | 1.0 | 1.0 |
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+ | 0.0916 | 8.0 | 24 | 0.0737 | 1.0 | 1.0 |
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+ | 0.0843 | 9.0 | 27 | 0.0656 | 1.0 | 1.0 |
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+ | 0.0701 | 10.0 | 30 | 0.0594 | 1.0 | 1.0 |
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+ | 0.0683 | 11.0 | 33 | 0.0546 | 1.0 | 1.0 |
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+ | 0.0599 | 12.0 | 36 | 0.0508 | 1.0 | 1.0 |
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+ | 0.058 | 13.0 | 39 | 0.0478 | 1.0 | 1.0 |
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+ | 0.0512 | 14.0 | 42 | 0.0454 | 1.0 | 1.0 |
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+ | 0.0523 | 15.0 | 45 | 0.0437 | 1.0 | 1.0 |
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+ | 0.0515 | 16.0 | 48 | 0.0423 | 1.0 | 1.0 |
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+ | 0.0468 | 17.0 | 51 | 0.0413 | 1.0 | 1.0 |
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+ | 0.0472 | 18.0 | 54 | 0.0406 | 1.0 | 1.0 |
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+ | 0.0479 | 19.0 | 57 | 0.0401 | 1.0 | 1.0 |
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+ | 0.0474 | 20.0 | 60 | 0.0400 | 1.0 | 1.0 |
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  ### Framework versions