---
base_model: cardiffnlp/twitter-xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: training_with_callbacks
  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. -->

# training_with_callbacks

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4317
- Precision: 0.7304
- Recall: 0.7613
- F1: 0.7456

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| No log        | 1.0   | 458  | 0.4317          | 0.7304    | 0.7613 | 0.7456 |
| 0.5107        | 2.0   | 916  | 0.4730          | 0.8008    | 0.6193 | 0.6985 |
| 0.3555        | 3.0   | 1374 | 0.4850          | 0.7512    | 0.7205 | 0.7355 |
| 0.2265        | 4.0   | 1832 | 0.6697          | 0.7379    | 0.7356 | 0.7368 |
| 0.1547        | 5.0   | 2290 | 0.7118          | 0.7491    | 0.6450 | 0.6932 |
| 0.1154        | 6.0   | 2748 | 1.0137          | 0.7177    | 0.7221 | 0.7199 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1