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vonewman
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wolof-finetuned-ner

Token Classification
Transformers
PyTorch
Safetensors
xlm-roberta
Generated from Trainer
Inference Endpoints
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Training complete

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  1. README.md +14 -14
  2. pytorch_model.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: 0.0716
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- - Precision: 0.8443
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- - Recall: 0.8299
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- - F1: 0.8370
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- - Accuracy: 0.9871
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  ## Model description
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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: 24
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- - eval_batch_size: 24
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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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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0373 | 1.0 | 76 | 0.0717 | 0.8805 | 0.7517 | 0.8110 | 0.9850 |
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- | 0.0256 | 2.0 | 152 | 0.0768 | 0.8176 | 0.8231 | 0.8203 | 0.9853 |
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- | 0.0184 | 3.0 | 228 | 0.0716 | 0.8443 | 0.8299 | 0.8370 | 0.9871 |
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  ### Framework versions
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- - Transformers 4.34.0
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.14.5
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- - Tokenizers 0.14.1
 
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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: 0.0781
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+ - Precision: 0.8227
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+ - Recall: 0.8367
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+ - F1: 0.8297
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+ - Accuracy: 0.9859
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  ## Model description
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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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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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 | 0.0955 | 0.7049 | 0.7313 | 0.7179 | 0.9806 |
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+ | No log | 2.0 | 452 | 0.0744 | 0.7816 | 0.8401 | 0.8098 | 0.9850 |
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+ | 0.1416 | 3.0 | 678 | 0.0781 | 0.8227 | 0.8367 | 0.8297 | 0.9859 |
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  ### Framework versions
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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
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