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README.md
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---
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base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
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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: cardiffnlp_twitter_roberta_base_sentiment_latest_Nov2023
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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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# cardiffnlp_twitter_roberta_base_sentiment_latest_Nov2023
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3189
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- Accuracy: 0.805
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 2
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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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| 0.6619 | 0.2 | 100 | 0.5226 | 0.6285 |
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| 0.4526 | 0.4 | 200 | 0.4150 | 0.716 |
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| 0.4092 | 0.6 | 300 | 0.3898 | 0.728 |
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| 0.3886 | 0.8 | 400 | 0.3441 | 0.773 |
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| 0.3822 | 1.0 | 500 | 0.3494 | 0.767 |
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| 0.3396 | 1.2 | 600 | 0.3470 | 0.7865 |
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| 0.3156 | 1.4 | 700 | 0.3418 | 0.7875 |
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| 0.3099 | 1.6 | 800 | 0.3231 | 0.794 |
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| 0.2994 | 1.8 | 900 | 0.3371 | 0.7885 |
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| 0.2907 | 2.0 | 1000 | 0.3189 | 0.805 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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