metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_uncased_L-2_H-128_A-2_rte
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE RTE
type: glue
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.6028880866425993
bert_uncased_L-2_H-128_A-2_rte
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6606
- Accuracy: 0.6029
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 |
|---|---|---|---|---|
| 0.6945 | 1.0 | 10 | 0.6932 | 0.4874 |
| 0.6914 | 2.0 | 20 | 0.6897 | 0.5271 |
| 0.6866 | 3.0 | 30 | 0.6866 | 0.5451 |
| 0.6812 | 4.0 | 40 | 0.6829 | 0.5415 |
| 0.676 | 5.0 | 50 | 0.6797 | 0.5668 |
| 0.6666 | 6.0 | 60 | 0.6769 | 0.5596 |
| 0.6596 | 7.0 | 70 | 0.6736 | 0.5740 |
| 0.6485 | 8.0 | 80 | 0.6693 | 0.5668 |
| 0.6347 | 9.0 | 90 | 0.6639 | 0.5884 |
| 0.6186 | 10.0 | 100 | 0.6625 | 0.6173 |
| 0.6026 | 11.0 | 110 | 0.6606 | 0.6029 |
| 0.5894 | 12.0 | 120 | 0.6638 | 0.6101 |
| 0.5841 | 13.0 | 130 | 0.6629 | 0.6065 |
| 0.566 | 14.0 | 140 | 0.6657 | 0.6101 |
| 0.5529 | 15.0 | 150 | 0.6673 | 0.5776 |
| 0.5312 | 16.0 | 160 | 0.6718 | 0.5812 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3