paraphrase-MiniLM-L12-v2-CoLA
This model is a fine-tuned version of sentence-transformers/paraphrase-MiniLM-L12-v2 on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.4636
- Matthews Correlation: 0.5057
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: 8e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 30198
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 16.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
---|---|---|---|---|
0.5747 | 1.0 | 67 | 0.5394 | 0.3455 |
0.5025 | 2.0 | 134 | 0.4999 | 0.4270 |
0.3698 | 3.0 | 201 | 0.4636 | 0.5057 |
0.2969 | 4.0 | 268 | 0.5309 | 0.4751 |
0.2275 | 5.0 | 335 | 0.6238 | 0.4775 |
0.1859 | 6.0 | 402 | 0.6315 | 0.4867 |
0.1517 | 7.0 | 469 | 0.7783 | 0.4695 |
0.1016 | 8.0 | 536 | 0.6762 | 0.4901 |
0.1017 | 9.0 | 603 | 0.7412 | 0.5046 |
0.0898 | 10.0 | 670 | 0.7719 | 0.4877 |
0.0527 | 11.0 | 737 | 0.8627 | 0.4955 |
0.0582 | 12.0 | 804 | 0.8986 | 0.4738 |
0.074 | 13.0 | 871 | 0.9469 | 0.4942 |
0.0508 | 14.0 | 938 | 0.9436 | 0.4918 |
0.024 | 15.0 | 1005 | 0.9391 | 0.4919 |
0.0458 | 16.0 | 1072 | 0.9375 | 0.4946 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.1
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Dataset used to train pszemraj/paraphrase-MiniLM-L12-v2-CoLA
Evaluation results
- Matthews Correlation on GLUE COLAvalidation set self-reported0.506