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End of training

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  1. README.md +10 -10
  2. pytorch_model.bin +1 -1
README.md CHANGED
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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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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7408
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  - name: F1
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  type: f1
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- value: 0.6839666291008939
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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 +34,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # amazon-reviews-finetuning-distilbert-base-uncased
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the amazon_reviews_multi dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6228
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- - Accuracy: 0.7408
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- - F1: 0.6840
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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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- | 0.6992 | 1.0 | 625 | 0.6202 | 0.74 | 0.6720 |
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- | 0.5651 | 2.0 | 1250 | 0.6228 | 0.7408 | 0.6840 |
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  ### Framework versions
 
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  ---
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+ license: mit
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+ base_model: nlptown/bert-base-multilingual-uncased-sentiment
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7576
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  - name: F1
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  type: f1
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+ value: 0.7044852616595344
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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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  # amazon-reviews-finetuning-distilbert-base-uncased
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+ This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the amazon_reviews_multi dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6020
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+ - Accuracy: 0.7576
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+ - F1: 0.7045
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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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+ | 0.6077 | 1.0 | 625 | 0.5697 | 0.7588 | 0.7045 |
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+ | 0.5097 | 2.0 | 1250 | 0.6020 | 0.7576 | 0.7045 |
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  ### Framework versions
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