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CuATR-distilbert-LoRA

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CuATR-distilbert-LoRA

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  1. README.md +15 -15
  2. adapter_model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6944
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- - Accuracy: 0.4348
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- - F1: 0.0
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  ## Model description
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@@ -52,18 +52,18 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
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- | 0.688 | 0.67 | 1 | 0.6963 | 0.4348 | 0.0 |
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- | 0.6869 | 2.0 | 3 | 0.6957 | 0.4348 | 0.0 |
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- | 0.699 | 2.67 | 4 | 0.6954 | 0.4348 | 0.0 |
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- | 0.7055 | 4.0 | 6 | 0.6952 | 0.4348 | 0.0 |
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- | 0.6813 | 4.67 | 7 | 0.6950 | 0.4348 | 0.0 |
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- | 0.6985 | 6.0 | 9 | 0.6947 | 0.4348 | 0.0 |
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- | 0.685 | 6.67 | 10 | 0.6946 | 0.4348 | 0.0 |
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- | 0.6865 | 8.0 | 12 | 0.6945 | 0.4348 | 0.0 |
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- | 0.6874 | 8.67 | 13 | 0.6944 | 0.4348 | 0.0 |
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- | 0.6984 | 9.33 | 14 | 0.6944 | 0.4348 | 0.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6945
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+ - Accuracy: 0.5652
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+ - F1: 0.7222
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.7007 | 0.67 | 1 | 0.6957 | 0.5652 | 0.7222 |
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+ | 0.6984 | 2.0 | 3 | 0.6954 | 0.5652 | 0.7222 |
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+ | 0.7075 | 2.67 | 4 | 0.6952 | 0.5652 | 0.7222 |
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+ | 0.7 | 4.0 | 6 | 0.6951 | 0.5652 | 0.7222 |
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+ | 0.6962 | 4.67 | 7 | 0.6950 | 0.5652 | 0.7222 |
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+ | 0.7003 | 6.0 | 9 | 0.6948 | 0.5652 | 0.7222 |
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+ | 0.6952 | 6.67 | 10 | 0.6947 | 0.5652 | 0.7222 |
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+ | 0.7027 | 8.0 | 12 | 0.6946 | 0.5652 | 0.7222 |
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+ | 0.6995 | 8.67 | 13 | 0.6946 | 0.5652 | 0.7222 |
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+ | 0.6919 | 9.33 | 14 | 0.6945 | 0.5652 | 0.7222 |
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  ### Framework versions
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