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loha_fine_tuned_cb_sloberta

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  1. README.md +12 -12
  2. adapter_model.safetensors +1 -1
  3. runs/May22_11-54-42_DESKTOP-22QTFDR/events.out.tfevents.1716371684.DESKTOP-22QTFDR.2016.6 +3 -0
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  8. runs/May22_12-26-10_DESKTOP-22QTFDR/events.out.tfevents.1716373615.DESKTOP-22QTFDR.2016.11 +3 -0
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  13. tokenizer.json +6 -1
  14. 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: 4.0446
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- - Accuracy: 0.5455
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- - F1: 0.5065
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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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- | 0.8849 | 3.5714 | 50 | 2.2562 | 0.3182 | 0.1536 |
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- | 0.7117 | 7.1429 | 100 | 1.0521 | 0.6364 | 0.6303 |
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- | 0.1154 | 10.7143 | 150 | 4.4399 | 0.4545 | 0.3964 |
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- | 0.0044 | 14.2857 | 200 | 3.0530 | 0.5455 | 0.5145 |
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- | 0.0008 | 17.8571 | 250 | 3.6707 | 0.5455 | 0.5065 |
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- | 0.0004 | 21.4286 | 300 | 4.1357 | 0.4545 | 0.3895 |
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- | 0.0002 | 25.0 | 350 | 4.0214 | 0.5455 | 0.5065 |
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- | 0.0001 | 28.5714 | 400 | 4.0446 | 0.5455 | 0.5065 |
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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: 2.2669
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+ - Accuracy: 0.6364
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+ - F1: 0.5977
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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: 0.002
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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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+ | 0.8405 | 3.5714 | 50 | 2.1784 | 0.3182 | 0.1536 |
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+ | 0.7138 | 7.1429 | 100 | 1.1353 | 0.5909 | 0.5636 |
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+ | 0.1766 | 10.7143 | 150 | 3.0435 | 0.5 | 0.4690 |
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+ | 0.0445 | 14.2857 | 200 | 2.1500 | 0.5909 | 0.5545 |
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+ | 0.0038 | 17.8571 | 250 | 1.7987 | 0.6364 | 0.5916 |
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+ | 0.001 | 21.4286 | 300 | 2.2097 | 0.6364 | 0.5977 |
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+ | 0.001 | 25.0 | 350 | 2.2794 | 0.6364 | 0.5977 |
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+ | 0.0016 | 28.5714 | 400 | 2.2669 | 0.6364 | 0.5977 |
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  ### Framework versions
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