---
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