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--- |
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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: finance_news_classifier |
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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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# finance_news_classifier |
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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: 1.1719 |
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- Accuracy: 0.8680 |
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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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| No log | 1.0 | 243 | 0.4023 | 0.8412 | |
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| No log | 2.0 | 486 | 0.4435 | 0.8526 | |
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| 0.3668 | 3.0 | 729 | 0.5688 | 0.8402 | |
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| 0.3668 | 4.0 | 972 | 0.6626 | 0.8598 | |
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| 0.1479 | 5.0 | 1215 | 0.8238 | 0.8557 | |
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| 0.1479 | 6.0 | 1458 | 0.9073 | 0.8536 | |
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| 0.0654 | 7.0 | 1701 | 0.9993 | 0.8557 | |
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| 0.0654 | 8.0 | 1944 | 1.0495 | 0.8526 | |
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| 0.0368 | 9.0 | 2187 | 1.1007 | 0.8392 | |
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| 0.0368 | 10.0 | 2430 | 1.1122 | 0.8505 | |
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| 0.0212 | 11.0 | 2673 | 1.1024 | 0.8680 | |
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| 0.0212 | 12.0 | 2916 | 1.0697 | 0.8670 | |
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| 0.0148 | 13.0 | 3159 | 1.1283 | 0.8639 | |
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| 0.0148 | 14.0 | 3402 | 1.1176 | 0.8701 | |
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| 0.008 | 15.0 | 3645 | 1.1625 | 0.8660 | |
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| 0.008 | 16.0 | 3888 | 1.1794 | 0.8639 | |
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| 0.0052 | 17.0 | 4131 | 1.1701 | 0.8629 | |
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| 0.0052 | 18.0 | 4374 | 1.1919 | 0.8608 | |
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| 0.005 | 19.0 | 4617 | 1.1745 | 0.8670 | |
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| 0.005 | 20.0 | 4860 | 1.1719 | 0.8680 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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