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--- |
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license: mit |
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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: Climate-TwitterBERT-xmas |
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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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# Climate-TwitterBERT-xmas |
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This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert-v2](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3348 |
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- Accuracy: 0.888 |
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- Precision: 0.7843 |
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- Recall: 0.7018 |
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- F1-weighted: 0.8857 |
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- F1: 0.7407 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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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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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 12 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1-weighted | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-----------:|:------:| |
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| 0.4411 | 3.64 | 50 | 0.3396 | 0.876 | 0.8611 | 0.5439 | 0.8652 | 0.6667 | |
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| 0.1872 | 7.27 | 100 | 0.3182 | 0.876 | 0.6912 | 0.8246 | 0.8796 | 0.7520 | |
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| 0.0724 | 10.91 | 150 | 0.3348 | 0.888 | 0.7843 | 0.7018 | 0.8857 | 0.7407 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.3 |
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