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rule_learning_margin_1mm_spanpred_nospec
enoriega/rule_learning_margin_1mm_spanpred_nospec
rule_learning_margin_1mm_spanpred_nospec is a machine learning model from enoriega. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jul 5, 2022
- Updated
- Jul 5, 2022
- SHA
- 5657f714
Datasets
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. -->
rule_learning_margin_1mm_spanpred_nospec
This model is a fine-tuned version of enoriega/rule_softmatching on the enoriega/odinsynth_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.3972
- Margin Accuracy: 0.8136
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2000
- total_train_batch_size: 8000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Margin Accuracy |
|---|---|---|---|---|
| 0.5864 | 0.16 | 20 | 0.5454 | 0.7564 |
| 0.4995 | 0.32 | 40 | 0.4761 | 0.7867 |
| 0.4866 | 0.48 | 60 | 0.4353 | 0.8057 |
| 0.4568 | 0.64 | 80 | 0.4229 | 0.8098 |
| 0.4409 | 0.8 | 100 | 0.4136 | 0.8140 |
| 0.4369 | 0.96 | 120 | 0.4124 | 0.8118 |
| 0.4172 | 1.12 | 140 | 0.4043 | 0.8118 |
| 0.4208 | 1.28 | 160 | 0.4072 | 0.8119 |
| 0.4256 | 1.44 | 180 | 0.4041 | 0.8124 |
| 0.4201 | 1.6 | 200 | 0.4041 | 0.8127 |
| 0.4159 | 1.76 | 220 | 0.4006 | 0.8125 |
| 0.4103 | 1.92 | 240 | 0.4004 | 0.8131 |
| 0.4282 | 2.08 | 260 | 0.3999 | 0.8138 |
| 0.4169 | 2.24 | 280 | 0.4006 | 0.8136 |
| 0.4263 | 2.4 | 300 | 0.3962 | 0.8133 |
| 0.4252 | 2.56 | 320 | 0.3994 | 0.8137 |
| 0.4202 | 2.72 | 340 | 0.3965 | 0.8137 |
| 0.4146 | 2.88 | 360 | 0.3967 | 0.8139 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.1
- Tokenizers 0.12.1
- Library
- transformers
- Type
- bert
- Created
- Jul 5, 2022
- Updated
- Jul 5, 2022