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---
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_3epoch10.2
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_3epoch10.2
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: 1.8545
- Accuracy: 0.7493
- F1: 0.4663
- Precision: 0.5984
- Recall: 0.3819
- Precision Sarcastic: 0.5984
- Recall Sarcastic: 0.3819
- F1 Sarcastic: 0.4663
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
| No log | 1.0 | 174 | 1.8493 | 0.7464 | 0.4323 | 0.6036 | 0.3367 | 0.6036 | 0.3367 | 0.4323 |
| No log | 2.0 | 348 | 1.5481 | 0.7522 | 0.5301 | 0.5808 | 0.4874 | 0.5808 | 0.4874 | 0.5301 |
| 0.0477 | 3.0 | 522 | 1.6249 | 0.7565 | 0.4531 | 0.6364 | 0.3518 | 0.6364 | 0.3518 | 0.4531 |
| 0.0477 | 4.0 | 696 | 1.6593 | 0.7464 | 0.4793 | 0.5827 | 0.4070 | 0.5827 | 0.4070 | 0.4793 |
| 0.0477 | 5.0 | 870 | 1.7213 | 0.7493 | 0.42 | 0.6238 | 0.3166 | 0.6238 | 0.3166 | 0.42 |
| 0.0277 | 6.0 | 1044 | 1.7249 | 0.7450 | 0.4381 | 0.5948 | 0.3467 | 0.5948 | 0.3467 | 0.4381 |
| 0.0277 | 7.0 | 1218 | 1.8038 | 0.7450 | 0.4486 | 0.5902 | 0.3618 | 0.5902 | 0.3618 | 0.4486 |
| 0.0277 | 8.0 | 1392 | 1.8409 | 0.7493 | 0.4387 | 0.6126 | 0.3417 | 0.6126 | 0.3417 | 0.4387 |
| 0.0105 | 9.0 | 1566 | 1.8427 | 0.7522 | 0.4487 | 0.6195 | 0.3518 | 0.6195 | 0.3518 | 0.4487 |
| 0.0105 | 10.0 | 1740 | 1.8545 | 0.7493 | 0.4663 | 0.5984 | 0.3819 | 0.5984 | 0.3819 | 0.4663 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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