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---
base_model: cardiffnlp/twitter-xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: twitter-xlm-roberta-finetuned-class
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-xlm-roberta-finetuned-class
This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7774
- F1: 0.7098
- Recall: 0.7333
- Accuracy: 0.7195
## 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: 1.7197827530913808e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 101
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|
| 0.9152 | 1.44 | 500 | 0.7553 | 0.7047 | 0.7156 | 0.7195 |
| 0.5205 | 2.87 | 1000 | 0.7774 | 0.7098 | 0.7333 | 0.7195 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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