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update model card README.md

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  license: apache-2.0
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  tags:
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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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  - f1
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  model-index:
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  - name: finetuning-sentiment-model-3000-samples
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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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- 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: 0.8666666666666667
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- - name: F1
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- type: f1
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- value: 0.8666666666666667
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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
@@ -31,11 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # finetuning-sentiment-model-3000-samples
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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: 0.3177
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- - Accuracy: 0.8667
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- - F1: 0.8667
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  ## Model description
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@@ -60,7 +44,7 @@ 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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  ### Framework versions
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- - Transformers 4.20.0
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  - Pytorch 1.11.0+cu113
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  - Datasets 2.3.2
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  - Tokenizers 0.12.1
 
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  - f1
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  model-index:
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  - name: finetuning-sentiment-model-3000-samples
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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
 
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  # finetuning-sentiment-model-3000-samples
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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: 0.7404
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+ - Accuracy: 0.4688
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+ - F1: 0.5526
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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: 1
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  ### Training results
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  ### Framework versions
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+ - Transformers 4.20.1
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  - Pytorch 1.11.0+cu113
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  - Datasets 2.3.2
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  - Tokenizers 0.12.1