End of training
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README.md
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---
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library_name: transformers
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base_model: cardiffnlp/twitter-roberta-base-sentiment
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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: test_trainer
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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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# test_trainer
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-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: 1.2587
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- Accuracy: 0.791
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- Micro F1: 0.791
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- Micro Precision: 0.791
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- Micro Recall: 0.791
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Micro F1 | Micro Precision | Micro Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|
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| No log | 1.0 | 438 | 1.0074 | 0.775 | 0.775 | 0.775 | 0.775 |
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| 0.1941 | 2.0 | 876 | 0.8466 | 0.789 | 0.789 | 0.789 | 0.789 |
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| 0.1976 | 3.0 | 1314 | 1.2587 | 0.791 | 0.791 | 0.791 | 0.791 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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runs/Nov25_10-51-14_7530b88aaa48/events.out.tfevents.1732532402.7530b88aaa48.662.2
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runs/Nov25_10-51-14_7530b88aaa48/events.out.tfevents.1732532878.7530b88aaa48.662.3
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