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--- |
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license: bigscience-bloom-rail-1.0 |
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base_model: bigscience/bloom-560m |
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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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model-index: |
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- name: SciBLOOM-ft-TweetAreas-ES |
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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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# SciBLOOM-ft-TweetAreas-ES |
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This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4180 |
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- Roc Auc: 0.8398 |
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- Hamming Loss: 0.0450 |
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- F1 Score: 0.7555 |
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- Accuracy: 0.4712 |
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- Precision: 0.8527 |
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- Recall: 0.7085 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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_steps: 500 |
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- num_epochs: 10 |
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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 | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:| |
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| 0.2275 | 1.0 | 747 | 0.3007 | 0.7245 | 0.0797 | 0.5268 | 0.2838 | 0.8290 | 0.4840 | |
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| 0.1338 | 2.0 | 1494 | 0.2027 | 0.7985 | 0.0611 | 0.6307 | 0.3788 | 0.7336 | 0.6296 | |
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| 0.1244 | 3.0 | 2241 | 0.1917 | 0.7985 | 0.0564 | 0.6552 | 0.4070 | 0.7901 | 0.6354 | |
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| 0.0459 | 4.0 | 2988 | 0.2264 | 0.8247 | 0.0535 | 0.7187 | 0.4110 | 0.8199 | 0.6832 | |
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| 0.046 | 5.0 | 3735 | 0.2932 | 0.8103 | 0.0541 | 0.6862 | 0.4003 | 0.8026 | 0.6552 | |
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| 0.0305 | 6.0 | 4482 | 0.3364 | 0.8318 | 0.0509 | 0.7236 | 0.4378 | 0.8015 | 0.7008 | |
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| 0.0075 | 7.0 | 5229 | 0.4112 | 0.8326 | 0.0482 | 0.7348 | 0.4418 | 0.8164 | 0.6929 | |
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| 0.001 | 8.0 | 5976 | 0.3984 | 0.8358 | 0.0466 | 0.7507 | 0.4538 | 0.8501 | 0.7022 | |
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| 0.0 | 9.0 | 6723 | 0.4134 | 0.8448 | 0.0454 | 0.7591 | 0.4712 | 0.8447 | 0.7198 | |
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| 0.0 | 10.0 | 7470 | 0.4180 | 0.8398 | 0.0450 | 0.7555 | 0.4712 | 0.8527 | 0.7085 | |
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### Framework versions |
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- Transformers 4.43.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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