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---
base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: xlm-roberta-meta4types-ft-2.0
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. -->
# xlm-roberta-meta4types-ft-2.0
This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0008
- Roc Auc: 0.6612
- Hamming Loss: 0.2239
- F1 Score: 0.5943
- Accuracy: 0.5392
- Precision: 0.5798
- Recall: 0.6121
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:|
| No log | 1.0 | 204 | 0.5010 | 0.4988 | 0.2042 | 0.2930 | 0.6127 | 0.5948 | 0.3333 |
| No log | 2.0 | 408 | 0.5433 | 0.5027 | 0.2010 | 0.3038 | 0.6176 | 0.9281 | 0.3388 |
| 0.4958 | 3.0 | 612 | 0.5013 | 0.5043 | 0.2010 | 0.3139 | 0.6127 | 0.8170 | 0.3443 |
| 0.4958 | 4.0 | 816 | 0.6563 | 0.6108 | 0.2190 | 0.5211 | 0.5686 | 0.6488 | 0.4799 |
| 0.3484 | 5.0 | 1020 | 0.6404 | 0.6444 | 0.1912 | 0.5645 | 0.5980 | 0.6014 | 0.5386 |
| 0.3484 | 6.0 | 1224 | 0.9555 | 0.6520 | 0.2614 | 0.5559 | 0.5196 | 0.5889 | 0.5417 |
| 0.3484 | 7.0 | 1428 | 0.7919 | 0.6202 | 0.2222 | 0.5417 | 0.5392 | 0.5743 | 0.5297 |
| 0.1644 | 8.0 | 1632 | 0.8959 | 0.6389 | 0.2157 | 0.5551 | 0.5539 | 0.5823 | 0.5515 |
| 0.1644 | 9.0 | 1836 | 1.0008 | 0.6612 | 0.2239 | 0.5943 | 0.5392 | 0.5798 | 0.6121 |
| 0.0611 | 10.0 | 2040 | 0.9594 | 0.6452 | 0.2141 | 0.5822 | 0.5294 | 0.5757 | 0.5893 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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