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--- |
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license: mit |
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base_model: xlnet-base-cased |
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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: xlnet-base-cased-tweets |
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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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# xlnet-base-cased-tweets |
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co./xlnet-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2693 |
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- Accuracy: 0.9287 |
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- F1: 0.9581 |
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- Precision: 0.9588 |
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- Recall: 0.9575 |
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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: 5e-05 |
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- train_batch_size: 16 |
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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: 5 |
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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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| 0.2517 | 1.0 | 642 | 0.3093 | 0.8804 | 0.9341 | 0.8799 | 0.9954 | |
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| 0.2239 | 2.0 | 1284 | 0.2935 | 0.9217 | 0.9542 | 0.9509 | 0.9575 | |
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| 0.2253 | 3.0 | 1926 | 0.2859 | 0.9170 | 0.9518 | 0.9422 | 0.9616 | |
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| 0.1936 | 4.0 | 2568 | 0.2904 | 0.9252 | 0.9559 | 0.9607 | 0.9511 | |
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| 0.1813 | 5.0 | 3210 | 0.2693 | 0.9287 | 0.9581 | 0.9588 | 0.9575 | |
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### Framework versions |
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- Transformers 4.43.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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