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  1. README.md +13 -13
  2. eval_results_ml.json +1 -1
  3. pytorch_model.bin +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -23,10 +23,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8000036435845584
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  - name: F1
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  type: f1
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- value: 0.758305292124411
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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
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the massive dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3801
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- - Accuracy: 0.8000
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- - F1: 0.7583
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  ## Model description
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@@ -69,14 +69,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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- | 0.489 | 0.56 | 5000 | 0.9200 | 0.7871 | 0.7332 |
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- | 0.2753 | 1.11 | 10000 | 1.0539 | 0.7885 | 0.7364 |
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- | 0.2348 | 1.67 | 15000 | 1.0362 | 0.7891 | 0.7431 |
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- | 0.1648 | 2.22 | 20000 | 1.1925 | 0.7867 | 0.7535 |
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- | 0.1481 | 2.78 | 25000 | 1.1608 | 0.7920 | 0.7513 |
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- | 0.1074 | 3.33 | 30000 | 1.3151 | 0.7966 | 0.7513 |
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- | 0.0942 | 3.89 | 35000 | 1.3274 | 0.7952 | 0.7523 |
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- | 0.0684 | 4.45 | 40000 | 1.3801 | 0.8000 | 0.7583 |
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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: 0.7999125539705962
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  - name: F1
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  type: f1
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+ value: 0.7608456488954072
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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 [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the massive dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3792
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+ - Accuracy: 0.7999
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+ - F1: 0.7608
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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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+ | 0.4658 | 0.56 | 5000 | 0.9703 | 0.7825 | 0.7290 |
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+ | 0.2748 | 1.11 | 10000 | 0.9829 | 0.7934 | 0.7386 |
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+ | 0.237 | 1.67 | 15000 | 1.0459 | 0.7881 | 0.7348 |
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+ | 0.1545 | 2.22 | 20000 | 1.1641 | 0.7920 | 0.7544 |
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+ | 0.1482 | 2.78 | 25000 | 1.1840 | 0.7951 | 0.7528 |
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+ | 0.1076 | 3.33 | 30000 | 1.2621 | 0.7933 | 0.7504 |
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+ | 0.0974 | 3.89 | 35000 | 1.3127 | 0.7972 | 0.7566 |
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+ | 0.0654 | 4.45 | 40000 | 1.3792 | 0.7999 | 0.7608 |
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  ### Framework versions
eval_results_ml.json CHANGED
@@ -1 +1 @@
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