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--- |
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base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment |
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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: fineTuningXLMRoberta-TokenClassification-Spacy |
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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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# fineTuningXLMRoberta-TokenClassification-Spacy |
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This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8479 |
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- Precision: 0.2076 |
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- Recall: 0.2102 |
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- F1: 0.2089 |
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- Accuracy: 0.6718 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 15 |
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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 | 31 | 0.7433 | 0.2164 | 0.1421 | 0.1716 | 0.6557 | |
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| No log | 2.0 | 62 | 0.7177 | 0.2275 | 0.1848 | 0.2039 | 0.6727 | |
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| No log | 3.0 | 93 | 0.7054 | 0.1719 | 0.1949 | 0.1827 | 0.6637 | |
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| No log | 4.0 | 124 | 0.7148 | 0.1823 | 0.1919 | 0.1869 | 0.6628 | |
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| No log | 5.0 | 155 | 0.7018 | 0.2063 | 0.2061 | 0.2062 | 0.6853 | |
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| No log | 6.0 | 186 | 0.7310 | 0.1866 | 0.1919 | 0.1892 | 0.6711 | |
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| No log | 7.0 | 217 | 0.7272 | 0.2150 | 0.2071 | 0.2110 | 0.6897 | |
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| No log | 8.0 | 248 | 0.7878 | 0.1758 | 0.1848 | 0.1802 | 0.6582 | |
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| No log | 9.0 | 279 | 0.7727 | 0.2080 | 0.2071 | 0.2075 | 0.6814 | |
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| No log | 10.0 | 310 | 0.8099 | 0.1969 | 0.1959 | 0.1964 | 0.6688 | |
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| No log | 11.0 | 341 | 0.8119 | 0.2062 | 0.2030 | 0.2046 | 0.6766 | |
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| No log | 12.0 | 372 | 0.8227 | 0.2105 | 0.2112 | 0.2108 | 0.6770 | |
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| No log | 13.0 | 403 | 0.8300 | 0.2008 | 0.2051 | 0.2029 | 0.6744 | |
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| No log | 14.0 | 434 | 0.8409 | 0.2064 | 0.2081 | 0.2073 | 0.6739 | |
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| No log | 15.0 | 465 | 0.8479 | 0.2076 | 0.2102 | 0.2089 | 0.6718 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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