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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: 0.92996
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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: 0.5305
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- - Accuracy: 0.9300
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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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- | 0.0405 | 1.0 | 1563 | 0.5220 | 0.9254 |
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- | 0.0177 | 2.0 | 3126 | 0.5305 | 0.9300 |
 
 
 
 
 
 
 
 
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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: 0.92984
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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: 0.6732
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+ - Accuracy: 0.9298
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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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+ | 0.0405 | 1.0 | 1563 | 0.9254 | 0.5220 |
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+ | 0.0177 | 2.0 | 3126 | 0.9300 | 0.5305 |
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+ | 0.0322 | 3.0 | 4689 | 0.9225 | 0.4810 |
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+ | 0.0122 | 4.0 | 6252 | 0.9244 | 0.5850 |
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+ | 0.0092 | 5.0 | 7815 | 0.5996 | 0.9282 |
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+ | 0.0064 | 6.0 | 9378 | 0.5723 | 0.9305 |
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+ | 0.0127 | 7.0 | 10941 | 0.6555 | 0.9283 |
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+ | 0.0035 | 8.0 | 12504 | 0.6549 | 0.9300 |
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+ | 0.0015 | 9.0 | 14067 | 0.6716 | 0.9288 |
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+ | 0.0004 | 10.0 | 15630 | 0.6732 | 0.9298 |
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  ### Framework versions