metadata
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Twroberta-baseB_5epoch
results: []
Twroberta-baseB_5epoch
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: 0.1414
- Accuracy: 0.7971
- Precision: 0.2686
- Recall: 0.3395
- F1: 0.2984
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 217 | 0.1259 | 0.8571 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 434 | 0.1252 | 0.8579 | 0.3690 | 0.0185 | 0.0351 |
| 0.1645 | 3.0 | 651 | 0.1203 | 0.8414 | 0.2958 | 0.2066 | 0.2431 |
| 0.1645 | 4.0 | 868 | 0.1383 | 0.7686 | 0.2221 | 0.3616 | 0.2751 |
| 0.0952 | 5.0 | 1085 | 0.1414 | 0.7971 | 0.2686 | 0.3395 | 0.2984 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1