End of training
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- pytorch_model.bin +1 -1
README.md
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datasets:
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- Jean-Baptiste/financial_news_sentiment_mixte_with_phrasebank_75
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pipeline_tag: text-classification
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tags:
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base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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- name: twitter_xlm_robertta_sentiment_financial_news
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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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# twitter_xlm_robertta_sentiment_financial_news
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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: 0.4492
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- F1: 0.8812
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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: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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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- lr_scheduler_warmup_steps: 300
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.518 | 1.0 | 556 | 0.4881 | 0.8184 |
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| 0.3534 | 2.0 | 1112 | 0.5041 | 0.8797 |
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| 0.1781 | 3.0 | 1668 | 0.4492 | 0.8812 |
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### Framework versions
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- Transformers 4.33.3
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.13.1
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pytorch_model.bin
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