metadata
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Twroberta-baseB_10epoch
results: []
Twroberta-baseB_10epoch
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-irony on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1763
- Accuracy: 0.7771
- Precision: 0.2366
- Recall: 0.3137
- F1: 0.2679
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 | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 217 | 0.1251 | 0.8571 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 434 | 0.1213 | 0.8571 | 0.0 | 0.0 | 0.0 |
| 0.1617 | 3.0 | 651 | 0.1226 | 0.8157 | 0.2655 | 0.3026 | 0.2828 |
| 0.1617 | 4.0 | 868 | 0.1423 | 0.7671 | 0.1991 | 0.2989 | 0.2389 |
| 0.0899 | 5.0 | 1085 | 0.1594 | 0.7364 | 0.2142 | 0.3727 | 0.2695 |
| 0.0899 | 6.0 | 1302 | 0.1560 | 0.8086 | 0.2567 | 0.2214 | 0.2320 |
| 0.0411 | 7.0 | 1519 | 0.1963 | 0.715 | 0.1945 | 0.3875 | 0.2584 |
| 0.0411 | 8.0 | 1736 | 0.1687 | 0.7914 | 0.2520 | 0.2804 | 0.2601 |
| 0.0411 | 9.0 | 1953 | 0.1726 | 0.7843 | 0.2419 | 0.2989 | 0.2646 |
| 0.0197 | 10.0 | 2170 | 0.1763 | 0.7771 | 0.2366 | 0.3137 | 0.2679 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1