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xlm-roberta-base-finetuned-wolof

Token Classification
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PyTorch
xlm-roberta
Generated from Trainer
Eval Results
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  1. README.md +14 -22
  2. pytorch_model.bin +1 -1
  3. tokenizer.json +2 -2
  4. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.8614609571788412
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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
@@ -32,8 +32,8 @@ 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 masakhaner2 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6731
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- - F1: 0.8615
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  ## Model description
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@@ -52,33 +52,25 @@ 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: 5e-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 | F1 |
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- |:-------------:|:-----:|:-----:|:---------------:|:------:|
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- | 0.6468 | 1.0 | 739 | 0.3680 | 0.7084 |
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- | 0.3085 | 2.0 | 1478 | 0.3194 | 0.7394 |
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- | 0.2155 | 3.0 | 2217 | 0.4131 | 0.7670 |
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- | 0.157 | 4.0 | 2956 | 0.3638 | 0.8077 |
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- | 0.1061 | 5.0 | 3695 | 0.3636 | 0.7819 |
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- | 0.08 | 6.0 | 4434 | 0.4743 | 0.8586 |
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- | 0.0593 | 7.0 | 5173 | 0.3827 | 0.8184 |
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- | 0.0332 | 8.0 | 5912 | 0.4892 | 0.8502 |
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- | 0.0244 | 9.0 | 6651 | 0.5380 | 0.8387 |
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- | 0.0206 | 10.0 | 7390 | 0.5505 | 0.8653 |
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- | 0.0119 | 11.0 | 8129 | 0.5966 | 0.8647 |
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- | 0.0064 | 12.0 | 8868 | 0.5154 | 0.8657 |
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- | 0.0036 | 13.0 | 9607 | 0.6321 | 0.8653 |
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- | 0.0028 | 14.0 | 10346 | 0.6662 | 0.8656 |
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- | 0.0014 | 15.0 | 11085 | 0.6731 | 0.8615 |
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  ### Framework versions
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.8514106583072101
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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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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the masakhaner2 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4671
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+ - F1: 0.8514
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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: 5.1193219561473124e-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: 7
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.6236 | 1.0 | 739 | 0.3714 | 0.7072 |
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+ | 0.296 | 2.0 | 1478 | 0.3902 | 0.7642 |
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+ | 0.1785 | 3.0 | 2217 | 0.3680 | 0.7728 |
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+ | 0.1222 | 4.0 | 2956 | 0.3825 | 0.8232 |
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+ | 0.0727 | 5.0 | 3695 | 0.3973 | 0.8274 |
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+ | 0.042 | 6.0 | 4434 | 0.5533 | 0.8460 |
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+ | 0.0233 | 7.0 | 5173 | 0.4671 | 0.8514 |
 
 
 
 
 
 
 
 
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  ### Framework versions
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