metadata
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cs605-nlp-assignment-2-bert-large-uncased-v2
results: []
cs605-nlp-assignment-2-bert-large-uncased-v2
This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4797
- Accuracy: 0.7861
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: 1.3166642758879955e-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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5698 | 1.0 | 746 | 0.4877 | 0.7533 |
0.4247 | 2.0 | 1492 | 0.5234 | 0.7777 |
0.1575 | 3.0 | 2238 | 0.6654 | 0.7741 |
0.1178 | 4.0 | 2984 | 1.0942 | 0.7764 |
0.044 | 5.0 | 3730 | 1.2965 | 0.7824 |
0.0345 | 6.0 | 4476 | 1.1750 | 0.7861 |
0.0164 | 7.0 | 5222 | 1.4659 | 0.7828 |
0.0136 | 8.0 | 5968 | 1.4372 | 0.7848 |
0.0059 | 9.0 | 6714 | 1.5201 | 0.7871 |
0.0081 | 10.0 | 7460 | 1.4797 | 0.7861 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1