bert_base_train_book_ent_40p_inv_mrpc
This model is a fine-tuned version of gokulsrinivasagan/bert_base_train_book_ent_40p_inv on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.6012
- Accuracy: 0.6765
- F1: 0.7822
- Combined Score: 0.7293
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 |
|---|---|---|---|---|---|---|
| 0.6473 | 1.0 | 15 | 0.6212 | 0.6642 | 0.7728 | 0.7185 |
| 0.5767 | 2.0 | 30 | 0.6012 | 0.6765 | 0.7822 | 0.7293 |
| 0.4762 | 3.0 | 45 | 0.6550 | 0.6814 | 0.7819 | 0.7316 |
| 0.3285 | 4.0 | 60 | 0.7622 | 0.6642 | 0.7486 | 0.7064 |
| 0.1756 | 5.0 | 75 | 1.1139 | 0.6814 | 0.7826 | 0.7320 |
| 0.0963 | 6.0 | 90 | 1.1768 | 0.6716 | 0.7657 | 0.7187 |
| 0.0766 | 7.0 | 105 | 1.2929 | 0.6618 | 0.7579 | 0.7098 |
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/bert_base_train_book_ent_40p_inv_mrpc
Base model
distilbert/distilbert-base-uncasedDataset used to train gokulsrinivasagan/bert_base_train_book_ent_40p_inv_mrpc
Evaluation results
- Accuracy on GLUE MRPCself-reported0.676
- F1 on GLUE MRPCself-reported0.782