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Training complete

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  1. README.md +66 -0
  2. config.json +2 -2
  3. pytorch_model.bin +2 -2
  4. tokenizer.json +2 -2
  5. tokenizer_config.json +8 -43
  6. training_args.bin +2 -2
README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: xlm-roberta-base-wolof
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # xlm-roberta-base-wolof
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+
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+ This model was trained from scratch on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2733
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+ - Precision: 0.7251
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+ - Recall: 0.7220
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+ - F1: 0.7236
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+ - Accuracy: 0.9586
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 4.899923663123727e-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: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 226 | 0.2416 | 0.7653 | 0.6519 | 0.7041 | 0.9587 |
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+ | No log | 2.0 | 452 | 0.2573 | 0.6917 | 0.7300 | 0.7104 | 0.9568 |
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+ | 0.0212 | 3.0 | 678 | 0.2733 | 0.7251 | 0.7220 | 0.7236 | 0.9586 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3
config.json CHANGED
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  {
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  "architectures": [
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  "XLMRobertaForTokenClassification"
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  ],
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