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loha_fine_tuned_rte_sloberta

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  1. README.md +12 -12
  2. adapter_model.safetensors +1 -1
  3. runs/May22_21-27-28_DESKTOP-22QTFDR/events.out.tfevents.1716406050.DESKTOP-22QTFDR.18964.2 +3 -0
  4. runs/May22_21-27-28_DESKTOP-22QTFDR/events.out.tfevents.1716406111.DESKTOP-22QTFDR.18964.3 +3 -0
  5. runs/May22_21-31-00_DESKTOP-22QTFDR/events.out.tfevents.1716406262.DESKTOP-22QTFDR.18964.4 +3 -0
  6. runs/May22_21-31-00_DESKTOP-22QTFDR/events.out.tfevents.1716406322.DESKTOP-22QTFDR.18964.5 +3 -0
  7. 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: 0.6921
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- - Accuracy: 0.5517
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- - F1: 0.5539
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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: 2e-05
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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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- | 0.6999 | 1.7241 | 50 | 0.6949 | 0.3793 | 0.3135 |
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- | 0.694 | 3.4483 | 100 | 0.6898 | 0.6207 | 0.5066 |
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- | 0.6931 | 5.1724 | 150 | 0.6948 | 0.4138 | 0.4040 |
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- | 0.6939 | 6.8966 | 200 | 0.6944 | 0.4483 | 0.4443 |
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- | 0.6956 | 8.6207 | 250 | 0.6921 | 0.5517 | 0.5539 |
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- | 0.6907 | 10.3448 | 300 | 0.6929 | 0.5517 | 0.5539 |
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- | 0.6905 | 12.0690 | 350 | 0.6924 | 0.5517 | 0.5539 |
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- | 0.689 | 13.7931 | 400 | 0.6921 | 0.5517 | 0.5539 |
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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.
21
  It achieves the following results on the evaluation set:
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+ - Loss: 0.6918
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+ - Accuracy: 0.6207
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+ - F1: 0.6179
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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: 1e-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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+ | 0.7008 | 1.7241 | 50 | 0.6873 | 0.5862 | 0.4333 |
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+ | 0.6935 | 3.4483 | 100 | 0.6873 | 0.5862 | 0.4333 |
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+ | 0.6949 | 5.1724 | 150 | 0.6907 | 0.5862 | 0.4854 |
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+ | 0.6941 | 6.8966 | 200 | 0.6923 | 0.5862 | 0.5862 |
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+ | 0.6956 | 8.6207 | 250 | 0.6918 | 0.6207 | 0.6179 |
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+ | 0.6917 | 10.3448 | 300 | 0.6922 | 0.5862 | 0.5862 |
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+ | 0.6914 | 12.0690 | 350 | 0.6920 | 0.6207 | 0.6179 |
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+ | 0.6901 | 13.7931 | 400 | 0.6918 | 0.6207 | 0.6179 |
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  ### Framework versions
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