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--- |
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license: mit |
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base_model: xlnet-large-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- recall |
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- precision |
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model-index: |
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- name: task2_xlnet-large-cased_3_4_2e-05_0.01 |
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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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# task2_xlnet-large-cased_3_4_2e-05_0.01 |
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This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/xlnet-large-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9482 |
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- F1: 0.7790 |
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- Recall: 0.7790 |
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- Precision: 0.7790 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:| |
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| 0.8074 | 1.0 | 745 | 0.7084 | 0.7574 | 0.7574 | 0.7574 | |
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| 0.7665 | 2.0 | 1490 | 0.7881 | 0.7628 | 0.7628 | 0.7628 | |
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| 0.6739 | 3.0 | 2235 | 0.9482 | 0.7790 | 0.7790 | 0.7790 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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