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--- |
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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: DistilBERTFINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False |
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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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# DistilBERTFINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False |
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2555 |
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- Precision: 1.0 |
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- Recall: 0.0200 |
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- F1: 0.0393 |
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- Accuracy: 0.0486 |
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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: 1e-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: 5 |
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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 | 95 | 0.5756 | nan | 0.0 | nan | 0.715 | |
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| No log | 2.0 | 190 | 0.5340 | 0.6429 | 0.1579 | 0.2535 | 0.735 | |
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| No log | 3.0 | 285 | 0.5298 | 0.5833 | 0.3684 | 0.4516 | 0.745 | |
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| No log | 4.0 | 380 | 0.5325 | 0.5789 | 0.3860 | 0.4632 | 0.745 | |
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| No log | 5.0 | 475 | 0.5452 | 0.4815 | 0.4561 | 0.4685 | 0.705 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.1+cu113 |
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- Datasets 1.18.0 |
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- Tokenizers 0.10.3 |
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