hBERTv1_new_pretrain_w_init_48_rte
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6910
- Accuracy: 0.5271
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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.712 | 1.0 | 20 | 0.7158 | 0.4729 |
0.7094 | 2.0 | 40 | 0.6958 | 0.4729 |
0.7025 | 3.0 | 60 | 0.7008 | 0.4729 |
0.705 | 4.0 | 80 | 0.6919 | 0.5271 |
0.7023 | 5.0 | 100 | 0.6960 | 0.5271 |
0.7002 | 6.0 | 120 | 0.7095 | 0.4729 |
0.7071 | 7.0 | 140 | 0.7040 | 0.4729 |
0.6982 | 8.0 | 160 | 0.6918 | 0.5271 |
0.7025 | 9.0 | 180 | 0.6910 | 0.5271 |
0.6965 | 10.0 | 200 | 0.6984 | 0.4621 |
0.6814 | 11.0 | 220 | 0.7635 | 0.4946 |
0.6616 | 12.0 | 240 | 0.6918 | 0.5271 |
0.6658 | 13.0 | 260 | 0.7622 | 0.5307 |
0.6316 | 14.0 | 280 | 0.8002 | 0.5090 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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