twitter_xlm_robertta_sentiment_financial_news
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on thishttps://huggingface.co/datasets/Jean-Baptiste/financial_news_sentiment_mixte_with_phrasebank_75 financial dataset. It achieves the following results on the evaluation set:
- Loss: 0.4492
- F1: 0.8812
Model description
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Intended uses & limitations
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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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.518 | 1.0 | 556 | 0.4881 | 0.8184 |
| 0.3534 | 2.0 | 1112 | 0.5041 | 0.8797 |
| 0.1781 | 3.0 | 1668 | 0.4492 | 0.8812 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.1
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