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---
base_model: cardiffnlp/twitter-roberta-base-irony
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Twroberta-baseB_15epoch
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. -->
# Twroberta-baseB_15epoch
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: 0.1971
- Accuracy: 0.7686
- Precision: 0.2328
- Recall: 0.3210
- F1: 0.2693
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 1.0 | 217 | 0.1248 | 0.8571 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 434 | 0.1250 | 0.8679 | 0.5258 | 0.0701 | 0.1237 |
| 0.1617 | 3.0 | 651 | 0.1225 | 0.825 | 0.2771 | 0.2657 | 0.2712 |
| 0.1617 | 4.0 | 868 | 0.1325 | 0.8079 | 0.3164 | 0.2583 | 0.2554 |
| 0.0885 | 5.0 | 1085 | 0.1553 | 0.7707 | 0.2169 | 0.2694 | 0.2391 |
| 0.0885 | 6.0 | 1302 | 0.1680 | 0.7507 | 0.2112 | 0.3358 | 0.2592 |
| 0.0392 | 7.0 | 1519 | 0.2129 | 0.7093 | 0.1936 | 0.3875 | 0.2575 |
| 0.0392 | 8.0 | 1736 | 0.1717 | 0.7764 | 0.2316 | 0.2841 | 0.2528 |
| 0.0392 | 9.0 | 1953 | 0.1915 | 0.7507 | 0.2287 | 0.3321 | 0.2671 |
| 0.0178 | 10.0 | 2170 | 0.1987 | 0.7586 | 0.2294 | 0.3653 | 0.2809 |
| 0.0178 | 11.0 | 2387 | 0.1923 | 0.7564 | 0.2287 | 0.3358 | 0.2710 |
| 0.0108 | 12.0 | 2604 | 0.1925 | 0.7586 | 0.2317 | 0.3358 | 0.2729 |
| 0.0108 | 13.0 | 2821 | 0.1965 | 0.775 | 0.2356 | 0.3284 | 0.2743 |
| 0.0078 | 14.0 | 3038 | 0.1964 | 0.7621 | 0.2326 | 0.3284 | 0.2712 |
| 0.0078 | 15.0 | 3255 | 0.1971 | 0.7686 | 0.2328 | 0.3210 | 0.2693 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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