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--- |
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license: mit |
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base_model: 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-ivrmenu-entity |
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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-ivrmenu-entity |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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- Precision: 0.8282 |
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- Recall: 0.8911 |
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- F1: 0.8585 |
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- Accuracy: 0.9345 |
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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: 0.0001 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 10 |
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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 | 2 | nan | 0.9036 | 0.4950 | 0.6397 | 0.6503 | |
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| No log | 2.0 | 4 | nan | 0.5952 | 0.5776 | 0.5863 | 0.7387 | |
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| No log | 3.0 | 6 | nan | 0.7124 | 0.7030 | 0.7076 | 0.8232 | |
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| No log | 4.0 | 8 | nan | 0.6879 | 0.7492 | 0.7172 | 0.8402 | |
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| No log | 5.0 | 10 | nan | 0.7333 | 0.7987 | 0.7646 | 0.8880 | |
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| No log | 6.0 | 12 | nan | 0.7462 | 0.8152 | 0.7792 | 0.9044 | |
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| No log | 7.0 | 14 | nan | 0.7761 | 0.8350 | 0.8045 | 0.9142 | |
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| No log | 8.0 | 16 | nan | 0.8145 | 0.8548 | 0.8341 | 0.9247 | |
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| No log | 9.0 | 18 | nan | 0.8185 | 0.8779 | 0.8471 | 0.9306 | |
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| No log | 10.0 | 20 | nan | 0.8282 | 0.8911 | 0.8585 | 0.9345 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.12.1 |
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