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README.md
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---
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license: mit
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base_model: FacebookAI/roberta-large
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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: RoBERTa-Large-full-finetuned-ner-pablo
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results: []
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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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# RoBERTa-Large-full-finetuned-ner-pablo
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This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1030
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- Precision: 0.8060
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- Recall: 0.7767
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- F1: 0.7910
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- Accuracy: 0.9711
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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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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| 0.3288 | 0.9996 | 652 | 0.1883 | 0.6920 | 0.6017 | 0.6437 | 0.9526 |
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| 0.1779 | 1.9992 | 1304 | 0.1474 | 0.6717 | 0.7175 | 0.6939 | 0.9600 |
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| 0.1471 | 2.9989 | 1956 | 0.1193 | 0.7544 | 0.7445 | 0.7494 | 0.9666 |
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| 0.1029 | 4.0 | 2609 | 0.1109 | 0.7757 | 0.7709 | 0.7733 | 0.9693 |
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| 0.0818 | 4.9981 | 3260 | 0.1030 | 0.8060 | 0.7767 | 0.7910 | 0.9711 |
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### Framework versions
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- Transformers 4.44.0
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- Pytorch 2.4.0+cu124
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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