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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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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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- f1 |
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- recall |
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- precision |
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model-index: |
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- name: tweet_sentiment_analysis_clean_tweet |
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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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# tweet_sentiment_analysis_clean_tweet |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4886 |
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- Accuracy: 0.8081 |
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- F1: 0.8073 |
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- Recall: 0.8037 |
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- Precision: 0.8110 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.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: 4 |
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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 | Recall | Precision | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:---------:| |
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| 0.4077 | 1.0 | 20000 | 0.4019 | 0.8153 | 0.8177 | 0.8281 | 0.8076 | |
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| 0.3382 | 2.0 | 40000 | 0.4175 | 0.8148 | 0.8133 | 0.8063 | 0.8204 | |
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| 0.2948 | 3.0 | 60000 | 0.4528 | 0.8107 | 0.8129 | 0.8220 | 0.8041 | |
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| 0.2541 | 4.0 | 80000 | 0.4886 | 0.8081 | 0.8073 | 0.8037 | 0.8110 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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