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End of training

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  1. README.md +16 -8
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@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.929
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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 imdb dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5406
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- - Accuracy: 0.929
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  ## Model description
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@@ -58,14 +58,22 @@ 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: 2
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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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- | 0.0473 | 1.0 | 1563 | 0.4618 | 0.9279 |
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- | 0.0096 | 2.0 | 3126 | 0.5406 | 0.929 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.93092
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7142
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+ - Accuracy: 0.9309
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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: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:--------:|:---------------:|
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+ | 0.0473 | 1.0 | 1563 | 0.9279 | 0.4618 |
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+ | 0.0096 | 2.0 | 3126 | 0.929 | 0.5406 |
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+ | 0.0328 | 3.0 | 4689 | 0.5954 | 0.92 |
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+ | 0.0192 | 4.0 | 6252 | 0.5570 | 0.9288 |
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+ | 0.0171 | 5.0 | 7815 | 0.5905 | 0.9294 |
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+ | 0.006 | 6.0 | 9378 | 0.6330 | 0.9301 |
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+ | 0.0084 | 7.0 | 10941 | 0.6311 | 0.9270 |
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+ | 0.0003 | 8.0 | 12504 | 0.6783 | 0.9288 |
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+ | 0.0048 | 9.0 | 14067 | 0.6987 | 0.9315 |
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+ | 0.0001 | 10.0 | 15630 | 0.7142 | 0.9309 |
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  ### Framework versions