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SciBERT_AsymmetricLoss_25K_bs64_P4_N1
bdpc/SciBERT_AsymmetricLoss_25K_bs64_P4_N1
SciBERT_AsymmetricLoss_25K_bs64_P4_N1 is a text classification model from bdpc. 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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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Feb 8, 2024
- Updated
- Feb 9, 2024
- SHA
- 4011776a
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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. -->
SciBERT_AsymmetricLoss_25K_bs64_P4_N1
This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 30.2502
- Accuracy: 0.9871
- Precision: 0.4247
- Recall: 0.8998
- F1: 0.5770
- Hamming: 0.0129
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 25000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming |
|---|---|---|---|---|---|---|---|---|
| 36.6287 | 0.16 | 5000 | 34.9978 | 0.9852 | 0.3863 | 0.8728 | 0.5355 | 0.0148 |
| 33.8929 | 0.32 | 10000 | 32.4942 | 0.9857 | 0.3958 | 0.8901 | 0.5480 | 0.0143 |
| 32.5419 | 0.47 | 15000 | 31.3170 | 0.9867 | 0.4162 | 0.8941 | 0.5680 | 0.0133 |
| 31.565 | 0.63 | 20000 | 30.6092 | 0.9869 | 0.4201 | 0.8975 | 0.5723 | 0.0131 |
| 31.105 | 0.79 | 25000 | 30.2502 | 0.9871 | 0.4247 | 0.8998 | 0.5770 | 0.0129 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.7.1
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Feb 8, 2024
- Updated
- Feb 9, 2024