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---
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tags:
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- generated_from_trainer
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model-index:
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- name: ind_roberta
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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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# ind_roberta
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-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: 0.5869
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- Accuracy@en: 0.9367
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- F1@en: 0.9349
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- Precision@en: 0.9321
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- Recall@en: 0.9389
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- Loss@en: 0.5869
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 4
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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: 13
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy@en | F1@en | Precision@en | Recall@en | Loss@en |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|:------------:|:---------:|:-------:|
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| 0.1056 | 1.0 | 375 | 0.3912 | 0.91 | 0.9069 | 0.9064 | 0.9074 | 0.3912 |
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| 0.0651 | 2.0 | 750 | 0.4985 | 0.9167 | 0.9146 | 0.9114 | 0.9195 | 0.4985 |
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| 0.1342 | 3.0 | 1125 | 0.4022 | 0.9233 | 0.9209 | 0.9194 | 0.9225 | 0.4022 |
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| 0.0982 | 4.0 | 1500 | 0.4177 | 0.9433 | 0.9418 | 0.9389 | 0.9458 | 0.4177 |
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| 0.0237 | 5.0 | 1875 | 0.5359 | 0.94 | 0.9386 | 0.9351 | 0.9443 | 0.5359 |
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| 0.0243 | 6.0 | 2250 | 0.5797 | 0.9233 | 0.9212 | 0.9185 | 0.9251 | 0.5797 |
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| 0.0377 | 7.0 | 2625 | 0.5550 | 0.94 | 0.9387 | 0.9350 | 0.9456 | 0.5550 |
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| 0.0001 | 8.0 | 3000 | 0.5920 | 0.9367 | 0.9353 | 0.9316 | 0.9428 | 0.5920 |
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| 0.0119 | 9.0 | 3375 | 0.5539 | 0.94 | 0.9387 | 0.9350 | 0.9456 | 0.5539 |
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| 0.0215 | 10.0 | 3750 | 0.5690 | 0.9433 | 0.9420 | 0.9384 | 0.9484 | 0.5690 |
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| 0.0146 | 11.0 | 4125 | 0.5687 | 0.9433 | 0.9420 | 0.9384 | 0.9484 | 0.5687 |
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| 0.0001 | 12.0 | 4500 | 0.5718 | 0.94 | 0.9386 | 0.9351 | 0.9443 | 0.5718 |
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| 0.0091 | 13.0 | 4875 | 0.5869 | 0.9367 | 0.9349 | 0.9321 | 0.9389 | 0.5869 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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