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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: roberta-finetuned-WebClassification-v2-smalllinguaESv2 |
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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-finetuned-WebClassification-v2-smalllinguaESv2 |
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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: 1.3862 |
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- Accuracy: 0.6909 |
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- F1: 0.6909 |
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- Precision: 0.6909 |
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- Recall: 0.6909 |
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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: 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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 28 | 2.9841 | 0.2 | 0.2000 | 0.2 | 0.2 | |
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| No log | 2.0 | 56 | 2.8109 | 0.1636 | 0.1636 | 0.1636 | 0.1636 | |
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| No log | 3.0 | 84 | 2.5334 | 0.3455 | 0.3455 | 0.3455 | 0.3455 | |
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| No log | 4.0 | 112 | 2.1164 | 0.5273 | 0.5273 | 0.5273 | 0.5273 | |
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| No log | 5.0 | 140 | 1.9152 | 0.5818 | 0.5818 | 0.5818 | 0.5818 | |
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| No log | 6.0 | 168 | 1.6678 | 0.6182 | 0.6182 | 0.6182 | 0.6182 | |
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| No log | 7.0 | 196 | 1.5647 | 0.6545 | 0.6545 | 0.6545 | 0.6545 | |
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| No log | 8.0 | 224 | 1.4473 | 0.6727 | 0.6727 | 0.6727 | 0.6727 | |
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| No log | 9.0 | 252 | 1.3862 | 0.6909 | 0.6909 | 0.6909 | 0.6909 | |
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| No log | 10.0 | 280 | 1.3647 | 0.6909 | 0.6909 | 0.6909 | 0.6909 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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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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