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prompt_fine_tuned_CB_sloberta

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prompt_fine_tuned_CB_sloberta

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  1. README.md +10 -10
  2. adapter_model.safetensors +1 -1
  3. runs/May22_13-09-15_DESKTOP-22QTFDR/events.out.tfevents.1716376155.DESKTOP-22QTFDR.10004.0 +3 -0
  4. runs/May22_13-09-15_DESKTOP-22QTFDR/events.out.tfevents.1716376166.DESKTOP-22QTFDR.10004.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -19,7 +19,7 @@ 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: 1.5600
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  - Accuracy: 0.3182
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  - F1: 0.1536
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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: 2e-05
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  - train_batch_size: 1
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  - eval_batch_size: 1
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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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- | 1.0277 | 0.4545 | 50 | 1.1402 | 0.3182 | 0.1536 |
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- | 0.8852 | 0.9091 | 100 | 1.1867 | 0.3182 | 0.1536 |
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- | 0.7108 | 1.3636 | 150 | 1.2699 | 0.3182 | 0.1536 |
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- | 0.8126 | 1.8182 | 200 | 1.3666 | 0.3182 | 0.1536 |
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- | 0.7952 | 2.2727 | 250 | 1.4335 | 0.3182 | 0.1536 |
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- | 0.7547 | 2.7273 | 300 | 1.5006 | 0.3182 | 0.1536 |
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- | 0.7687 | 3.1818 | 350 | 1.5424 | 0.3182 | 0.1536 |
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- | 0.6684 | 3.6364 | 400 | 1.5600 | 0.3182 | 0.1536 |
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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: 3.3650
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  - Accuracy: 0.3182
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  - F1: 0.1536
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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: 1
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  - eval_batch_size: 1
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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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+ | 1.5028 | 0.4545 | 50 | 5.1956 | 0.3182 | 0.1591 |
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+ | 2.1341 | 0.9091 | 100 | 4.9336 | 0.3182 | 0.1536 |
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+ | 1.2666 | 1.3636 | 150 | 5.4769 | 0.3182 | 0.1536 |
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+ | 1.7486 | 1.8182 | 200 | 4.4089 | 0.3182 | 0.1536 |
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+ | 1.5321 | 2.2727 | 250 | 3.3006 | 0.4545 | 0.3895 |
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+ | 1.296 | 2.7273 | 300 | 3.3196 | 0.3182 | 0.1536 |
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+ | 1.3419 | 3.1818 | 350 | 3.1575 | 0.3182 | 0.1536 |
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+ | 1.0893 | 3.6364 | 400 | 3.3650 | 0.3182 | 0.1536 |
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  ### Framework versions
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