metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-CLS-RTE
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: rte
split: validation
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.6967509025270758
bert-base-uncased-finetuned-CLS-RTE
This model is a fine-tuned version of bert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 2.2843
- Accuracy: 0.6968
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 156 | 0.6285 | 0.6390 |
| No log | 2.0 | 312 | 0.6483 | 0.6679 |
| No log | 3.0 | 468 | 0.8430 | 0.7004 |
| 0.4504 | 4.0 | 624 | 1.2886 | 0.6606 |
| 0.4504 | 5.0 | 780 | 1.6445 | 0.7004 |
| 0.4504 | 6.0 | 936 | 1.8099 | 0.6751 |
| 0.0631 | 7.0 | 1092 | 1.8173 | 0.7040 |
| 0.0631 | 8.0 | 1248 | 1.9799 | 0.7004 |
| 0.0631 | 9.0 | 1404 | 1.9767 | 0.6968 |
| 0.0159 | 10.0 | 1560 | 2.1696 | 0.6715 |
| 0.0159 | 11.0 | 1716 | 2.2142 | 0.6859 |
| 0.0159 | 12.0 | 1872 | 2.2605 | 0.6823 |
| 0.0076 | 13.0 | 2028 | 2.2775 | 0.7040 |
| 0.0076 | 14.0 | 2184 | 2.2719 | 0.6968 |
| 0.0076 | 15.0 | 2340 | 2.2843 | 0.6968 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0