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xlm-roberta-base-finetuned-ner-thesis-dseb

Token Classification
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xlm-roberta
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  1. README.md +23 -20
  2. model.safetensors +1 -1
  3. runs/Jul05_10-21-52_cfaea0d34aeb/events.out.tfevents.1720175042.cfaea0d34aeb.278.0 +3 -0
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  5. runs/Jul05_10-26-50_cfaea0d34aeb/events.out.tfevents.1720175213.cfaea0d34aeb.278.2 +3 -0
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  10. runs/Jul05_10-34-54_cfaea0d34aeb/events.out.tfevents.1720175831.cfaea0d34aeb.278.7 +3 -0
  11. tokenizer.json +2 -2
  12. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1313
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  - Precision: 0.0
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  - Recall: 0.0
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  - F1: 0.0
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- - Accuracy: 0.9315
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  ## Model description
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@@ -43,30 +43,33 @@ 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: 4
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- - eval_batch_size: 32
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  - seed: 42
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 8
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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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- - num_epochs: 10
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 0.9091 | 5 | 0.7631 | 0.0 | 0.0 | 0.0 | 0.9368 |
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- | No log | 2.0 | 11 | 0.2917 | 0.0 | 0.0 | 0.0 | 0.9430 |
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- | No log | 2.9091 | 16 | 0.2146 | 0.0 | 0.0 | 0.0 | 0.9430 |
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- | 0.5371 | 4.0 | 22 | 0.1465 | 0.0 | 0.0 | 0.0 | 0.9430 |
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- | 0.5371 | 4.9091 | 27 | 0.1146 | 0.0 | 0.0 | 0.0 | 0.9430 |
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- | 0.5371 | 6.0 | 33 | 0.0938 | 0.0 | 0.0 | 0.0 | 0.9430 |
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- | 0.5371 | 6.9091 | 38 | 0.0865 | 0.0 | 0.0 | 0.0 | 0.9430 |
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- | 0.1459 | 8.0 | 44 | 0.0824 | 0.0 | 0.0 | 0.0 | 0.9456 |
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- | 0.1459 | 8.9091 | 49 | 0.0797 | 0.0833 | 0.0714 | 0.0769 | 0.9514 |
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- | 0.1459 | 9.0909 | 50 | 0.0797 | 0.0833 | 0.0714 | 0.0769 | 0.9514 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6324
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  - Precision: 0.0
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  - Recall: 0.0
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  - F1: 0.0
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+ - Accuracy: 0.7314
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 15
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.5604 | 1.0 | 12 | 0.2449 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.141 | 2.0 | 24 | 0.2360 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.1111 | 3.0 | 36 | 0.2263 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.0939 | 4.0 | 48 | 0.1960 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.1069 | 5.0 | 60 | 0.1867 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.0818 | 6.0 | 72 | 0.1879 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.0614 | 7.0 | 84 | 0.1510 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.0622 | 8.0 | 96 | 0.1348 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.0633 | 9.0 | 108 | 0.1674 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.0427 | 10.0 | 120 | 0.1632 | 0.0 | 0.0 | 0.0 | 0.9593 |
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+ | 0.0389 | 11.0 | 132 | 0.1546 | 0.0 | 0.0 | 0.0 | 0.9590 |
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+ | 0.0344 | 12.0 | 144 | 0.1754 | 0.125 | 0.0312 | 0.05 | 0.9618 |
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+ | 0.0342 | 13.0 | 156 | 0.1702 | 0.0 | 0.0 | 0.0 | 0.9611 |
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+ | 0.0272 | 14.0 | 168 | 0.1739 | 0.0526 | 0.0312 | 0.0392 | 0.9623 |
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+ | 0.0224 | 15.0 | 180 | 0.1759 | 0.0526 | 0.0312 | 0.0392 | 0.9630 |
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  ### Framework versions
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