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README.md
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---
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library_name: transformers
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license: mit
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base_model: cardiffnlp/twitter-roberta-large-hate-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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- precision
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- recall
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- f1
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model-index:
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- name: twitter-roberta-large-hate-latest-roman-urdu-fine-grained
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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-roberta-large-hate-latest-roman-urdu-fine-grained
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-large-hate-latest](https://huggingface.co/cardiffnlp/twitter-roberta-large-hate-latest) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4394
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- Accuracy: 0.8521
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- Precision: 0.7814
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- Recall: 0.7733
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- F1: 0.7764
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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: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 128
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.8983 | 0.9912 | 56 | 0.7694 | 0.7359 | 0.6713 | 0.6012 | 0.6247 |
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| 0.7237 | 2.0 | 113 | 0.5778 | 0.7987 | 0.7241 | 0.6824 | 0.6913 |
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| 0.5471 | 2.9912 | 169 | 0.4937 | 0.8297 | 0.7491 | 0.7530 | 0.7503 |
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| 0.5403 | 4.0 | 226 | 0.4589 | 0.8424 | 0.7705 | 0.7575 | 0.7626 |
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| 0.5452 | 4.9558 | 280 | 0.4394 | 0.8521 | 0.7814 | 0.7733 | 0.7764 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.4.0
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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