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jysh1023
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bert_uncased_L-6_H-768_A-12-QAT

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Files changed (3) hide show
  1. README.md +10 -10
  2. logs/events.out.tfevents.1700301264.1d5d6d420ef6.278.28 +2 -2
  3. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.908256880733945
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/bert_uncased_L-6_H-768_A-12](https://huggingface.co/google/bert_uncased_L-6_H-768_A-12) on the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2640
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- - Accuracy: 0.9083
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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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- | 0.2383 | 1.0 | 527 | 0.2640 | 0.9083 |
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- | 0.1211 | 2.0 | 1054 | 0.2745 | 0.9037 |
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- | 0.0794 | 3.0 | 1581 | 0.2862 | 0.9048 |
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- | 0.0532 | 4.0 | 2108 | 0.3184 | 0.9060 |
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- | 0.037 | 5.0 | 2635 | 0.3778 | 0.9037 |
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- | 0.0231 | 6.0 | 3162 | 0.4477 | 0.8968 |
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- | 0.0156 | 7.0 | 3689 | 0.5036 | 0.8979 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8979357798165137
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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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  This model is a fine-tuned version of [google/bert_uncased_L-6_H-768_A-12](https://huggingface.co/google/bert_uncased_L-6_H-768_A-12) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5514
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+ - Accuracy: 0.8979
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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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+ | 0.0485 | 1.0 | 527 | 0.3517 | 0.8819 |
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+ | 0.0862 | 2.0 | 1054 | 0.3239 | 0.9094 |
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+ | 0.0538 | 3.0 | 1581 | 0.2942 | 0.9083 |
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+ | 0.0354 | 4.0 | 2108 | 0.3710 | 0.9071 |
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+ | 0.0248 | 5.0 | 2635 | 0.3842 | 0.9002 |
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+ | 0.0152 | 6.0 | 3162 | 0.4606 | 0.8956 |
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+ | 0.0105 | 7.0 | 3689 | 0.5514 | 0.8979 |
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  ### Framework versions
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