Training complete
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README.md
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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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# wolof-finetuned-ner
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This model
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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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:
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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 | 1.0 | 226 | 0.
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| No log | 2.0 | 452 | 0.
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### Framework versions
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---
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license: mit
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base_model: vonewman/xlm-roberta-base-finetuned-wolof
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tags:
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- generated_from_trainer
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metrics:
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# wolof-finetuned-ner
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This model is a fine-tuned version of [vonewman/xlm-roberta-base-finetuned-wolof](https://huggingface.co/vonewman/xlm-roberta-base-finetuned-wolof) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2937
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- Precision: 0.8082
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- Recall: 0.8741
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- F1: 0.8399
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- Accuracy: 0.9871
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## Model description
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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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### 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 | 1.0 | 226 | 0.2625 | 0.7522 | 0.8571 | 0.8013 | 0.9846 |
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| No log | 2.0 | 452 | 0.3009 | 0.7857 | 0.8605 | 0.8214 | 0.9854 |
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| 0.365 | 3.0 | 678 | 0.2937 | 0.8082 | 0.8741 | 0.8399 | 0.9871 |
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### Framework versions
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