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README.md
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---
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base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
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tags:
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- generated_from_trainer
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model-index:
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- name: Analisis-sentimientos-XLM-Roberta-TASS
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Analisis-sentimientos-XLM-Roberta-TASS
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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.
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It achieves the following results on the evaluation set:
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- Loss: 2.9837
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- Rmse: 0.7071
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rmse |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 1.0334 | 1.0 | 156 | 0.9397 | 0.9439 |
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| 0.7612 | 2.0 | 312 | 1.1421 | 0.7250 |
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| 0.5843 | 3.0 | 468 | 1.5608 | 0.7026 |
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| 0.2322 | 4.0 | 624 | 2.1870 | 0.6554 |
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| 0.143 | 5.0 | 780 | 2.3847 | 0.7553 |
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| 0.0953 | 6.0 | 936 | 2.3580 | 0.6841 |
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| 0.027 | 7.0 | 1092 | 2.7096 | 0.6980 |
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| 0.0103 | 8.0 | 1248 | 3.0068 | 0.7161 |
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| 0.007 | 9.0 | 1404 | 2.9551 | 0.7026 |
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| 0.0045 | 10.0 | 1560 | 2.9837 | 0.7071 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.18.0
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- Tokenizers 0.13.3
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