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lora_fine_tuned_copa_croslo

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lora_fine_tuned_copa_croslo

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Files changed (7) hide show
  1. README.md +12 -12
  2. adapter_model.safetensors +1 -1
  3. runs/May21_18-05-35_DESKTOP-22QTFDR/events.out.tfevents.1716307536.DESKTOP-22QTFDR.9252.2 +3 -0
  4. runs/May21_18-05-35_DESKTOP-22QTFDR/events.out.tfevents.1716307557.DESKTOP-22QTFDR.9252.3 +3 -0
  5. special_tokens_map.json +35 -5
  6. tokenizer.json +8 -1
  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/crosloengual-bert](https://huggingface.co/EMBEDDIA/crosloengual-bert) 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: 0.46
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- - F1: 0.46
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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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- | 0.7145 | 1.0 | 50 | 0.6931 | 0.54 | 0.5411 |
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- | 0.7231 | 2.0 | 100 | 0.6931 | 0.42 | 0.4214 |
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- | 0.717 | 3.0 | 150 | 0.6931 | 0.48 | 0.4813 |
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- | 0.7176 | 4.0 | 200 | 0.6931 | 0.49 | 0.4913 |
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- | 0.7024 | 5.0 | 250 | 0.6931 | 0.46 | 0.4600 |
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- | 0.6977 | 6.0 | 300 | 0.6931 | 0.52 | 0.52 |
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- | 0.7335 | 7.0 | 350 | 0.6931 | 0.48 | 0.48 |
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- | 0.708 | 8.0 | 400 | 0.6931 | 0.46 | 0.46 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [EMBEDDIA/crosloengual-bert](https://huggingface.co/EMBEDDIA/crosloengual-bert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6871
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+ - Accuracy: 0.52
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+ - F1: 0.5212
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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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+ | 0.6985 | 1.0 | 50 | 0.6889 | 0.52 | 0.5212 |
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+ | 0.7039 | 2.0 | 100 | 0.6885 | 0.52 | 0.5212 |
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+ | 0.7019 | 3.0 | 150 | 0.6879 | 0.52 | 0.5212 |
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+ | 0.6908 | 4.0 | 200 | 0.6875 | 0.52 | 0.5212 |
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+ | 0.6922 | 5.0 | 250 | 0.6872 | 0.52 | 0.5212 |
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+ | 0.6978 | 6.0 | 300 | 0.6871 | 0.52 | 0.5212 |
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+ | 0.6884 | 7.0 | 350 | 0.6871 | 0.52 | 0.5212 |
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+ | 0.6972 | 8.0 | 400 | 0.6871 | 0.52 | 0.5212 |
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  ### Framework versions
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