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Vs2882
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liar_binaryclassifier_bert_cased

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End of training

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Files changed (3) hide show
  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. runs/Oct14_08-21-59_06443fd34229/events.out.tfevents.1728894126.06443fd34229.321.0 +2 -2
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.6572668112798264
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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
@@ -33,9 +33,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the liar dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6241
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  - Model Preparation Time: 0.0032
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- - Accuracy: 0.6573
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|
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- | 0.6762 | 1.0 | 461 | 0.6389 | 0.0032 | 0.6616 |
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- | 0.6392 | 2.0 | 922 | 0.6249 | 0.0032 | 0.6616 |
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- | 0.6056 | 3.0 | 1383 | 0.6210 | 0.0032 | 0.6638 |
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- | 0.5701 | 4.0 | 1844 | 0.6220 | 0.0032 | 0.6616 |
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- | 0.553 | 5.0 | 2305 | 0.6241 | 0.0032 | 0.6573 |
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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: 0.648590021691974
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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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the liar dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6331
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  - Model Preparation Time: 0.0032
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+ - Accuracy: 0.6486
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|
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+ | 0.6826 | 1.0 | 461 | 0.6477 | 0.0032 | 0.6117 |
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+ | 0.6435 | 2.0 | 922 | 0.6267 | 0.0032 | 0.6356 |
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+ | 0.6131 | 3.0 | 1383 | 0.6302 | 0.0032 | 0.6529 |
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+ | 0.5809 | 4.0 | 1844 | 0.6233 | 0.0032 | 0.6508 |
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+ | 0.5658 | 5.0 | 2305 | 0.6331 | 0.0032 | 0.6486 |
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  ### Framework versions
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