metadata
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-cased-massive_intent
results: []
bert-large-cased-massive_intent
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6377
- Accuracy: 0.8942
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.6229 | 1.0 | 1440 | 1.1695 | 0.7718 |
| 0.9067 | 2.0 | 2880 | 0.6360 | 0.8603 |
| 0.4804 | 3.0 | 4320 | 0.5548 | 0.8746 |
| 0.3044 | 4.0 | 5760 | 0.5343 | 0.8913 |
| 0.2077 | 5.0 | 7200 | 0.6043 | 0.8913 |
| 0.1442 | 6.0 | 8640 | 0.6377 | 0.8942 |
| 0.1096 | 7.0 | 10080 | 0.6919 | 0.8888 |
| 0.0796 | 8.0 | 11520 | 0.7272 | 0.8908 |
| 0.0622 | 9.0 | 12960 | 0.7530 | 0.8918 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1