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lora_fine_tuned_copa_sloberta

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Files changed (6) hide show
  1. README.md +12 -12
  2. adapter_config.json +1 -1
  3. adapter_model.safetensors +2 -2
  4. runs/May21_19-20-30_DESKTOP-22QTFDR/events.out.tfevents.1716312032.DESKTOP-22QTFDR.34588.6 +3 -0
  5. runs/May21_19-20-30_DESKTOP-22QTFDR/events.out.tfevents.1716312058.DESKTOP-22QTFDR.34588.7 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [EMBEDDIA/sloberta](https://huggingface.co/EMBEDDIA/sloberta) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6931
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- - Accuracy: 0.47
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- - F1: 0.4533
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  ## Model description
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@@ -40,7 +40,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.003
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -52,14 +52,14 @@ 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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- | 0.698 | 1.0 | 50 | 0.6931 | 0.47 | 0.4606 |
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- | 0.6955 | 2.0 | 100 | 0.6931 | 0.5 | 0.4861 |
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- | 0.7099 | 3.0 | 150 | 0.6931 | 0.49 | 0.4838 |
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- | 0.6962 | 4.0 | 200 | 0.6931 | 0.58 | 0.5713 |
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- | 0.702 | 5.0 | 250 | 0.6931 | 0.44 | 0.4409 |
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- | 0.6869 | 6.0 | 300 | 0.6931 | 0.54 | 0.5332 |
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- | 0.7083 | 7.0 | 350 | 0.6931 | 0.57 | 0.5564 |
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- | 0.6959 | 8.0 | 400 | 0.6931 | 0.47 | 0.4533 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [EMBEDDIA/sloberta](https://huggingface.co/EMBEDDIA/sloberta) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6924
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+ - Accuracy: 0.61
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+ - F1: 0.6110
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6918 | 1.0 | 50 | 0.6925 | 0.59 | 0.5909 |
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+ | 0.6913 | 2.0 | 100 | 0.6929 | 0.57 | 0.5709 |
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+ | 0.6927 | 3.0 | 150 | 0.6925 | 0.56 | 0.5607 |
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+ | 0.6931 | 4.0 | 200 | 0.6926 | 0.56 | 0.5607 |
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+ | 0.6932 | 5.0 | 250 | 0.6925 | 0.59 | 0.5910 |
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+ | 0.6942 | 6.0 | 300 | 0.6924 | 0.6 | 0.6010 |
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+ | 0.6958 | 7.0 | 350 | 0.6924 | 0.61 | 0.6110 |
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+ | 0.6941 | 8.0 | 400 | 0.6924 | 0.61 | 0.6110 |
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  ### Framework versions
adapter_config.json CHANGED
@@ -1,7 +1,7 @@
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  {
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  "alpha_pattern": {},
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  "inference_mode": true,
 
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