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bioBERT-finetuned-biopharma-dive
daniel-gordon/bioBERT-finetuned-biopharma-dive
bioBERT-finetuned-biopharma-dive is a text classification model from daniel-gordon. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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.safetensors433 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Dec 9, 2023
- Updated
- Dec 9, 2023
- SHA
- 5fc847a0
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bioBERT-finetuned-biopharma-dive
This model is a fine-tuned version of daniel-gordon/bioBERT-finetuned-financial-phrasebank on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9018
- F1: 0.6009
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 110 | 0.9018 | 0.6009 |
| No log | 2.0 | 220 | 0.9249 | 0.5851 |
| No log | 3.0 | 330 | 1.0173 | 0.5835 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Dec 9, 2023
- Updated
- Dec 9, 2023