tinybert_train_book_ent_15p_inv_mrpc
This model is a fine-tuned version of gokulsrinivasagan/tinybert_train_book_ent_15p_inv on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.5824
- Accuracy: 0.6912
- F1: 0.7968
- Combined Score: 0.7440
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.6271 | 1.0 | 15 | 0.6072 | 0.7059 | 0.8148 | 0.7603 |
| 0.5897 | 2.0 | 30 | 0.5824 | 0.6912 | 0.7968 | 0.7440 |
| 0.5555 | 3.0 | 45 | 0.6068 | 0.7157 | 0.8237 | 0.7697 |
| 0.5055 | 4.0 | 60 | 0.6074 | 0.6863 | 0.7681 | 0.7272 |
| 0.4197 | 5.0 | 75 | 0.6650 | 0.6961 | 0.7832 | 0.7396 |
| 0.3231 | 6.0 | 90 | 0.8156 | 0.6765 | 0.7763 | 0.7264 |
| 0.2398 | 7.0 | 105 | 0.8915 | 0.6740 | 0.7734 | 0.7237 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for gokulsrinivasagan/tinybert_train_book_ent_15p_inv_mrpc
Base model
distilbert/distilbert-base-uncasedDataset used to train gokulsrinivasagan/tinybert_train_book_ent_15p_inv_mrpc
Evaluation results
- Accuracy on GLUE MRPCself-reported0.691
- F1 on GLUE MRPCself-reported0.797