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twitter_xlm_robertta_sentiment_financial_news
Alberto/twitter_xlm_robertta_sentiment_financial_news
twitter_xlm_robertta_sentiment_financial_news is a text classification model from Alberto. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023
- SHA
- e60b29af
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
More information needed
Intended uses & limitations
More information needed
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
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023