|
--- |
|
base_model: cardiffnlp/twitter-roberta-base-irony |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- precision |
|
- recall |
|
model-index: |
|
- name: twitter-roberta-base_3epoch5 |
|
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. --> |
|
|
|
# twitter-roberta-base_3epoch5 |
|
|
|
This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-irony](https://huggingface.co/cardiffnlp/twitter-roberta-base-irony) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.7195 |
|
- Accuracy: 0.7738 |
|
- F1: 0.5341 |
|
- Precision: 0.6522 |
|
- Recall: 0.4523 |
|
- Precision Sarcastic: 0.6522 |
|
- Recall Sarcastic: 0.4523 |
|
- F1 Sarcastic: 0.5341 |
|
|
|
## 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 | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:| |
|
| No log | 1.0 | 174 | 1.9750 | 0.7695 | 0.4702 | 0.6893 | 0.3568 | 0.6893 | 0.3568 | 0.4702 | |
|
| No log | 2.0 | 348 | 1.8774 | 0.7695 | 0.5062 | 0.656 | 0.4121 | 0.656 | 0.4121 | 0.5062 | |
|
| 0.027 | 3.0 | 522 | 2.0072 | 0.7738 | 0.5016 | 0.6810 | 0.3970 | 0.6810 | 0.3970 | 0.5016 | |
|
| 0.027 | 4.0 | 696 | 1.6484 | 0.7622 | 0.5299 | 0.6118 | 0.4673 | 0.6118 | 0.4673 | 0.5299 | |
|
| 0.027 | 5.0 | 870 | 1.7195 | 0.7738 | 0.5341 | 0.6522 | 0.4523 | 0.6522 | 0.4523 | 0.5341 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
