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---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bertweet-base-finetuned-filtered-0609
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bertweet-base-finetuned-filtered-0609
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5397
- Accuracy: 0.9299
- Precision: 0.9297
- Recall: 0.9299
- F1: 0.9298
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.331 | 1.0 | 3180 | 0.3687 | 0.9069 | 0.9147 | 0.9069 | 0.9081 |
| 0.2611 | 2.0 | 6360 | 0.3725 | 0.9223 | 0.9227 | 0.9223 | 0.9224 |
| 0.1993 | 3.0 | 9540 | 0.2948 | 0.9336 | 0.9350 | 0.9336 | 0.9339 |
| 0.1648 | 4.0 | 12720 | 0.3563 | 0.9296 | 0.9303 | 0.9296 | 0.9298 |
| 0.1324 | 5.0 | 15900 | 0.4136 | 0.9267 | 0.9279 | 0.9267 | 0.9270 |
| 0.1102 | 6.0 | 19080 | 0.4060 | 0.9352 | 0.9357 | 0.9352 | 0.9353 |
| 0.0568 | 7.0 | 22260 | 0.4653 | 0.9321 | 0.9328 | 0.9321 | 0.9322 |
| 0.0292 | 8.0 | 25440 | 0.4818 | 0.9311 | 0.9310 | 0.9311 | 0.9310 |
| 0.0155 | 9.0 | 28620 | 0.5405 | 0.9286 | 0.9288 | 0.9286 | 0.9286 |
| 0.0095 | 10.0 | 31800 | 0.5397 | 0.9299 | 0.9297 | 0.9299 | 0.9298 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.9.1+cu111
- Datasets 1.16.1
- Tokenizers 0.12.1
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