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test_TwoWayLoss_25K_bs64_P4_N1
bdpc/test_TwoWayLoss_25K_bs64_P4_N1
test_TwoWayLoss_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 8, 2024
- SHA
- 9510d238
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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. -->
test_TwoWayLoss_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: 8.8668
- Accuracy: 0.5430
- Precision: 0.0114
- Recall: 0.5359
- F1: 0.0224
- Hamming: 0.4570
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: 8
- eval_batch_size: 8
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming |
|---|---|---|---|---|---|---|---|---|
| 8.9097 | 0.0 | 5 | 8.8974 | 0.5287 | 0.0107 | 0.5189 | 0.0210 | 0.4713 |
| 8.1387 | 0.0 | 10 | 8.8668 | 0.5430 | 0.0114 | 0.5359 | 0.0224 | 0.4570 |
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 8, 2024