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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 +14 -14
  2. adapter_model.safetensors +1 -1
  3. runs/May22_13-31-27_DESKTOP-22QTFDR/events.out.tfevents.1716377489.DESKTOP-22QTFDR.10004.8 +3 -0
  4. runs/May22_13-31-27_DESKTOP-22QTFDR/events.out.tfevents.1716377526.DESKTOP-22QTFDR.10004.9 +3 -0
  5. 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: 3.3650
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  - Accuracy: 0.3182
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- - F1: 0.1536
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  ## Model description
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@@ -41,8 +41,8 @@ More information needed
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
@@ -50,16 +50,16 @@ 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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- | 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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  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: 1.7179
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  - Accuracy: 0.3182
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+ - F1: 0.1591
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  ## Model description
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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
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.8289 | 3.5714 | 50 | 1.9695 | 0.3182 | 0.1536 |
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+ | 0.7265 | 7.1429 | 100 | 1.4997 | 0.3636 | 0.2273 |
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+ | 0.6323 | 10.7143 | 150 | 1.4937 | 0.3636 | 0.2891 |
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+ | 0.5933 | 14.2857 | 200 | 1.7106 | 0.2727 | 0.2290 |
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+ | 0.5496 | 17.8571 | 250 | 1.3607 | 0.3636 | 0.2821 |
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+ | 0.4356 | 21.4286 | 300 | 1.4913 | 0.3182 | 0.1536 |
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+ | 0.3874 | 25.0 | 350 | 1.6290 | 0.2727 | 0.1527 |
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+ | 0.3719 | 28.5714 | 400 | 1.7179 | 0.3182 | 0.1591 |
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  ### Framework versions
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