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rdsmaia
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my_awesome_model

Text Classification
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distilbert
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End of training

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  1. README.md +9 -24
  2. model.safetensors +1 -1
README.md CHANGED
@@ -3,26 +3,11 @@ license: apache-2.0
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  base_model: distilbert-base-uncased
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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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  model-index:
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  - name: my_awesome_model
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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: 0.93088
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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
@@ -30,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # my_awesome_model
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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: 0.2374
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- - Accuracy: 0.9309
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  ## Model description
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@@ -64,13 +49,13 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.2235 | 1.0 | 1563 | 0.1968 | 0.9246 |
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- | 0.14 | 2.0 | 3126 | 0.2374 | 0.9309 |
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  ### Framework versions
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- - Transformers 4.36.0
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- - Pytorch 2.1.0+cu118
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- - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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  base_model: distilbert-base-uncased
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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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  model-index:
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  - name: my_awesome_model
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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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  # my_awesome_model
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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: 0.2310
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+ - Accuracy: 0.9313
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.224 | 1.0 | 1563 | 0.1983 | 0.9234 |
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+ | 0.1475 | 2.0 | 3126 | 0.2310 | 0.9313 |
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  ### Framework versions
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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  - Tokenizers 0.15.0
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