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README.md
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---
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license: mit
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base_model: roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: roberta_twitterfin_padding100model
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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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# roberta_twitterfin_padding100model
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8974
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- Accuracy: 0.9062
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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: 16
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- eval_batch_size: 16
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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: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.6161 | 1.0 | 597 | 0.3067 | 0.8836 |
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| 0.3154 | 2.0 | 1194 | 0.2813 | 0.9003 |
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| 0.2524 | 3.0 | 1791 | 0.4237 | 0.8903 |
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| 0.191 | 4.0 | 2388 | 0.3915 | 0.8974 |
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| 0.1607 | 5.0 | 2985 | 0.5921 | 0.8794 |
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| 0.0813 | 6.0 | 3582 | 0.6027 | 0.8920 |
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| 0.0867 | 7.0 | 4179 | 0.7093 | 0.8882 |
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| 0.0601 | 8.0 | 4776 | 0.6902 | 0.8920 |
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| 0.0578 | 9.0 | 5373 | 0.7902 | 0.8886 |
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| 0.0565 | 10.0 | 5970 | 0.7581 | 0.9003 |
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| 0.0322 | 11.0 | 6567 | 0.8172 | 0.8945 |
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| 0.0189 | 12.0 | 7164 | 0.7463 | 0.8961 |
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| 0.0283 | 13.0 | 7761 | 0.7960 | 0.9054 |
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| 0.0219 | 14.0 | 8358 | 0.8057 | 0.9033 |
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| 0.0168 | 15.0 | 8955 | 0.7975 | 0.9075 |
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| 0.0103 | 16.0 | 9552 | 0.8289 | 0.9012 |
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| 0.0074 | 17.0 | 10149 | 0.8471 | 0.9037 |
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| 0.0083 | 18.0 | 10746 | 0.8944 | 0.9041 |
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| 0.0061 | 19.0 | 11343 | 0.8967 | 0.9049 |
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| 0.0019 | 20.0 | 11940 | 0.8974 | 0.9062 |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 2.1.1
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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