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Training completed!

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  ---
 
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  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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- - emotion
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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: distilbert-base-uncased-finetuned-emotion
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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: emotion
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- type: emotion
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- config: split
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- split: validation
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- args: split
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- metrics:
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- - name: Accuracy
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- type: accuracy
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- value: 0.9215
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- - name: F1
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- type: f1
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- value: 0.9214718883562769
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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
@@ -34,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert-base-uncased-finetuned-emotion
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2186
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- - Accuracy: 0.9215
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- - F1: 0.9215
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.8382 | 1.0 | 250 | 0.3176 | 0.905 | 0.9037 |
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- | 0.2522 | 2.0 | 500 | 0.2186 | 0.9215 | 0.9215 |
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  ### Framework versions
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- - Transformers 4.40.2
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- - Pytorch 2.2.2+cu121
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- - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  ---
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+ library_name: transformers
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  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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  metrics:
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  - accuracy
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  - f1
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  model-index:
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  - name: distilbert-base-uncased-finetuned-emotion
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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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  # distilbert-base-uncased-finetuned-emotion
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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: 0.2117
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+ - Accuracy: 0.9275
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+ - F1: 0.9275
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.8106 | 1.0 | 250 | 0.3030 | 0.908 | 0.9064 |
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+ | 0.2435 | 2.0 | 500 | 0.2117 | 0.9275 | 0.9275 |
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  ### Framework versions
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+ - Transformers 4.44.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.21.0
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  - Tokenizers 0.19.1