---
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
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# 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