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Intradiction
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BERT-SA-LORA

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  1. README.md +13 -8
  2. adapter_model.safetensors +1 -1
  3. runs/Mar15_16-07-19_c9face729cf4/events.out.tfevents.1710518840.c9face729cf4.247.5 +2 -2
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4047
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- - Accuracy: 0.835
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  ## Model description
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@@ -44,17 +44,22 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 125 | 0.6581 | 0.639 |
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- | No log | 2.0 | 250 | 0.5742 | 0.716 |
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- | No log | 3.0 | 375 | 0.4301 | 0.817 |
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- | 0.5534 | 4.0 | 500 | 0.3904 | 0.837 |
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- | 0.5534 | 5.0 | 625 | 0.4047 | 0.835 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3776
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+ - Accuracy: 0.873
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 125 | 0.5379 | 0.74 |
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+ | No log | 2.0 | 250 | 0.4962 | 0.78 |
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+ | No log | 3.0 | 375 | 0.4127 | 0.827 |
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+ | 0.4731 | 4.0 | 500 | 0.3871 | 0.849 |
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+ | 0.4731 | 5.0 | 625 | 0.3720 | 0.861 |
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+ | 0.4731 | 6.0 | 750 | 0.4096 | 0.858 |
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+ | 0.4731 | 7.0 | 875 | 0.3971 | 0.869 |
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+ | 0.2887 | 8.0 | 1000 | 0.3856 | 0.868 |
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+ | 0.2887 | 9.0 | 1125 | 0.3751 | 0.872 |
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+ | 0.2887 | 10.0 | 1250 | 0.3776 | 0.873 |
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  ### Framework versions
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