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End of training

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  1. README.md +45 -8
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@@ -5,9 +5,24 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - imdb
 
 
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  model-index:
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  - name: distilbert_imdb_padding100model
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -16,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert_imdb_padding100model
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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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  ## Model description
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@@ -40,18 +58,37 @@ 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: 0.01
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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 | 0.01 | 16 | 0.6877 | 0.5020 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.32.1
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- - Pytorch 2.1.1
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- - Datasets 2.12.0
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  - Tokenizers 0.13.3
 
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  - generated_from_trainer
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  datasets:
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  - imdb
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+ metrics:
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+ - accuracy
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  model-index:
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  - name: distilbert_imdb_padding100model
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: imdb
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+ type: imdb
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+ config: plain_text
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+ split: test
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+ args: plain_text
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9298
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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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  # distilbert_imdb_padding100model
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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: 0.7577
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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: 20
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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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+ | 0.24 | 1.0 | 1563 | 0.2377 | 0.9178 |
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+ | 0.1837 | 2.0 | 3126 | 0.2434 | 0.926 |
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+ | 0.1183 | 3.0 | 4689 | 0.3062 | 0.9256 |
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+ | 0.0725 | 4.0 | 6252 | 0.3338 | 0.9271 |
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+ | 0.0455 | 5.0 | 7815 | 0.4833 | 0.9156 |
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+ | 0.0436 | 6.0 | 9378 | 0.4745 | 0.9260 |
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+ | 0.0257 | 7.0 | 10941 | 0.4971 | 0.9254 |
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+ | 0.0235 | 8.0 | 12504 | 0.5366 | 0.9226 |
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+ | 0.0219 | 9.0 | 14067 | 0.5533 | 0.9244 |
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+ | 0.0219 | 10.0 | 15630 | 0.5323 | 0.9267 |
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+ | 0.0122 | 11.0 | 17193 | 0.7565 | 0.9170 |
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+ | 0.012 | 12.0 | 18756 | 0.6422 | 0.9261 |
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+ | 0.0068 | 13.0 | 20319 | 0.6996 | 0.9265 |
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+ | 0.0055 | 14.0 | 21882 | 0.7342 | 0.9269 |
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+ | 0.0135 | 15.0 | 23445 | 0.7324 | 0.9252 |
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+ | 0.0053 | 16.0 | 25008 | 0.6880 | 0.9288 |
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+ | 0.001 | 17.0 | 26571 | 0.7319 | 0.9289 |
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+ | 0.0015 | 18.0 | 28134 | 0.7300 | 0.9287 |
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+ | 0.0016 | 19.0 | 29697 | 0.7450 | 0.9294 |
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+ | 0.0001 | 20.0 | 31260 | 0.7577 | 0.9298 |
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  ### Framework versions
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+ - Transformers 4.33.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.5
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  - Tokenizers 0.13.3