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--- |
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base_model: vinai/bertweet-base |
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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: bertweet-base_3epoch10.2 |
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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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# bertweet-base_3epoch10.2 |
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This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co./vinai/bertweet-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8545 |
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- Accuracy: 0.7493 |
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- F1: 0.4663 |
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- Precision: 0.5984 |
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- Recall: 0.3819 |
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- Precision Sarcastic: 0.5984 |
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- Recall Sarcastic: 0.3819 |
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- F1 Sarcastic: 0.4663 |
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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: 16 |
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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 | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:| |
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| No log | 1.0 | 174 | 1.8493 | 0.7464 | 0.4323 | 0.6036 | 0.3367 | 0.6036 | 0.3367 | 0.4323 | |
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| No log | 2.0 | 348 | 1.5481 | 0.7522 | 0.5301 | 0.5808 | 0.4874 | 0.5808 | 0.4874 | 0.5301 | |
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| 0.0477 | 3.0 | 522 | 1.6249 | 0.7565 | 0.4531 | 0.6364 | 0.3518 | 0.6364 | 0.3518 | 0.4531 | |
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| 0.0477 | 4.0 | 696 | 1.6593 | 0.7464 | 0.4793 | 0.5827 | 0.4070 | 0.5827 | 0.4070 | 0.4793 | |
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| 0.0477 | 5.0 | 870 | 1.7213 | 0.7493 | 0.42 | 0.6238 | 0.3166 | 0.6238 | 0.3166 | 0.42 | |
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| 0.0277 | 6.0 | 1044 | 1.7249 | 0.7450 | 0.4381 | 0.5948 | 0.3467 | 0.5948 | 0.3467 | 0.4381 | |
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| 0.0277 | 7.0 | 1218 | 1.8038 | 0.7450 | 0.4486 | 0.5902 | 0.3618 | 0.5902 | 0.3618 | 0.4486 | |
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| 0.0277 | 8.0 | 1392 | 1.8409 | 0.7493 | 0.4387 | 0.6126 | 0.3417 | 0.6126 | 0.3417 | 0.4387 | |
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| 0.0105 | 9.0 | 1566 | 1.8427 | 0.7522 | 0.4487 | 0.6195 | 0.3518 | 0.6195 | 0.3518 | 0.4487 | |
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| 0.0105 | 10.0 | 1740 | 1.8545 | 0.7493 | 0.4663 | 0.5984 | 0.3819 | 0.5984 | 0.3819 | 0.4663 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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