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--- |
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library_name: transformers |
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license: cc-by-4.0 |
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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: mca-sentiment-analyzer-v2 |
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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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# mca-sentiment-analyzer-v2 |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1090 |
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- Accuracy: 0.9668 |
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- F1 Macro: 0.9673 |
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- F1 Weighted: 0.9669 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
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| 1.2893 | 0.1559 | 20 | 0.9350 | 0.6074 | 0.4810 | 0.4802 | |
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| 0.8368 | 0.3119 | 40 | 0.5051 | 0.8848 | 0.8833 | 0.8831 | |
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| 0.6255 | 0.4678 | 60 | 0.2471 | 0.9336 | 0.9341 | 0.9336 | |
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| 0.469 | 0.6238 | 80 | 0.1967 | 0.9297 | 0.9299 | 0.9295 | |
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| 0.3423 | 0.7797 | 100 | 0.1227 | 0.9551 | 0.9558 | 0.9553 | |
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| 0.3477 | 0.9357 | 120 | 0.1090 | 0.9668 | 0.9673 | 0.9669 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.0 |
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