metadata
base_model: vinai/bertweet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bertweet-base_3epoch
results: []
bertweet-base_3epoch
This model is a fine-tuned version of vinai/bertweet-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5247
- Accuracy: 0.7565
- F1: 0.3424
- Precision: 0.7586
- Recall: 0.2211
- Precision Sarcastic: 0.7586
- Recall Sarcastic: 0.2211
- F1 Sarcastic: 0.3424
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
---|---|---|---|---|---|---|---|---|---|---|
No log | 1.0 | 174 | 0.6037 | 0.7133 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 2.0 | 348 | 0.6196 | 0.7133 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
0.5432 | 3.0 | 522 | 0.5247 | 0.7565 | 0.3424 | 0.7586 | 0.2211 | 0.7586 | 0.2211 | 0.3424 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1