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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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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: bertweet-base-finetuned-filtered-0609 |
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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-finetuned-filtered-0609 |
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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: 0.5397 |
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- Accuracy: 0.9299 |
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- Precision: 0.9297 |
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- Recall: 0.9299 |
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- F1: 0.9298 |
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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: 8 |
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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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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.331 | 1.0 | 3180 | 0.3687 | 0.9069 | 0.9147 | 0.9069 | 0.9081 | |
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| 0.2611 | 2.0 | 6360 | 0.3725 | 0.9223 | 0.9227 | 0.9223 | 0.9224 | |
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| 0.1993 | 3.0 | 9540 | 0.2948 | 0.9336 | 0.9350 | 0.9336 | 0.9339 | |
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| 0.1648 | 4.0 | 12720 | 0.3563 | 0.9296 | 0.9303 | 0.9296 | 0.9298 | |
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| 0.1324 | 5.0 | 15900 | 0.4136 | 0.9267 | 0.9279 | 0.9267 | 0.9270 | |
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| 0.1102 | 6.0 | 19080 | 0.4060 | 0.9352 | 0.9357 | 0.9352 | 0.9353 | |
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| 0.0568 | 7.0 | 22260 | 0.4653 | 0.9321 | 0.9328 | 0.9321 | 0.9322 | |
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| 0.0292 | 8.0 | 25440 | 0.4818 | 0.9311 | 0.9310 | 0.9311 | 0.9310 | |
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| 0.0155 | 9.0 | 28620 | 0.5405 | 0.9286 | 0.9288 | 0.9286 | 0.9286 | |
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| 0.0095 | 10.0 | 31800 | 0.5397 | 0.9299 | 0.9297 | 0.9299 | 0.9298 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.9.1+cu111 |
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- Datasets 1.16.1 |
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- Tokenizers 0.12.1 |
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