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--- |
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license: apache-2.0 |
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base_model: google/muril-base-cased |
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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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- accuracy |
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model-index: |
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- name: output |
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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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# output |
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This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6250 |
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- Precision: 0.7716 |
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- Recall: 0.7647 |
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- Accuracy: 0.7647 |
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- F1-score: 0.7587 |
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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: 2e-05 |
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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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- 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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1-score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:| |
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| 1.7858 | 1.0 | 32 | 1.7821 | 0.0454 | 0.2130 | 0.2130 | 0.0748 | |
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| 1.7526 | 2.0 | 64 | 1.7539 | 0.1754 | 0.2860 | 0.2860 | 0.1866 | |
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| 1.7112 | 3.0 | 96 | 1.7232 | 0.3352 | 0.3043 | 0.3043 | 0.2168 | |
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| 1.6655 | 4.0 | 128 | 1.6832 | 0.7122 | 0.6166 | 0.6166 | 0.6194 | |
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| 1.6217 | 5.0 | 160 | 1.6496 | 0.7708 | 0.7688 | 0.7688 | 0.7629 | |
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| 1.5898 | 6.0 | 192 | 1.6431 | 0.7618 | 0.7424 | 0.7424 | 0.7379 | |
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| 1.5678 | 7.0 | 224 | 1.6285 | 0.7697 | 0.7627 | 0.7627 | 0.7565 | |
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| 1.5572 | 8.0 | 256 | 1.6250 | 0.7716 | 0.7647 | 0.7647 | 0.7587 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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