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---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_intent
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert_intent
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0169
- Accuracy: 0.9982
## 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: 1e-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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2615 | 1.0 | 692 | 0.0516 | 0.9809 |
| 0.0191 | 2.0 | 1384 | 0.0231 | 0.9947 |
| 0.0083 | 3.0 | 2076 | 0.0140 | 0.9982 |
| 0.0051 | 4.0 | 2768 | 0.0101 | 0.9975 |
| 0.0028 | 5.0 | 3460 | 0.0075 | 0.9979 |
| 0.0013 | 6.0 | 4152 | 0.0064 | 0.9979 |
| 0.0008 | 7.0 | 4844 | 0.0073 | 0.9979 |
| 0.0004 | 8.0 | 5536 | 0.0069 | 0.9979 |
| 0.0003 | 9.0 | 6228 | 0.0072 | 0.9979 |
| 0.0002 | 10.0 | 6920 | 0.0075 | 0.9979 |
| 0.0002 | 11.0 | 7612 | 0.0077 | 0.9979 |
| 0.0001 | 12.0 | 8304 | 0.0080 | 0.9979 |
| 0.0001 | 13.0 | 8996 | 0.0083 | 0.9979 |
| 0.0001 | 14.0 | 9688 | 0.0087 | 0.9979 |
| 0.0 | 15.0 | 10380 | 0.0093 | 0.9979 |
| 0.0 | 16.0 | 11072 | 0.0097 | 0.9982 |
| 0.0 | 17.0 | 11764 | 0.0096 | 0.9979 |
| 0.0 | 18.0 | 12456 | 0.0106 | 0.9979 |
| 0.0 | 19.0 | 13148 | 0.0108 | 0.9979 |
| 0.0 | 20.0 | 13840 | 0.0110 | 0.9979 |
| 0.0 | 21.0 | 14532 | 0.0111 | 0.9979 |
| 0.0 | 22.0 | 15224 | 0.0116 | 0.9979 |
| 0.0 | 23.0 | 15916 | 0.0116 | 0.9979 |
| 0.0 | 24.0 | 16608 | 0.0125 | 0.9982 |
| 0.0 | 25.0 | 17300 | 0.0130 | 0.9982 |
| 0.0 | 26.0 | 17992 | 0.0124 | 0.9979 |
| 0.0 | 27.0 | 18684 | 0.0129 | 0.9979 |
| 0.0 | 28.0 | 19376 | 0.0138 | 0.9982 |
| 0.0 | 29.0 | 20068 | 0.0140 | 0.9982 |
| 0.0 | 30.0 | 20760 | 0.0145 | 0.9982 |
| 0.0 | 31.0 | 21452 | 0.0144 | 0.9982 |
| 0.0 | 32.0 | 22144 | 0.0146 | 0.9982 |
| 0.0 | 33.0 | 22836 | 0.0152 | 0.9982 |
| 0.0 | 34.0 | 23528 | 0.0151 | 0.9982 |
| 0.0 | 35.0 | 24220 | 0.0151 | 0.9982 |
| 0.0 | 36.0 | 24912 | 0.0153 | 0.9982 |
| 0.0 | 37.0 | 25604 | 0.0155 | 0.9982 |
| 0.0 | 38.0 | 26296 | 0.0158 | 0.9982 |
| 0.0 | 39.0 | 26988 | 0.0159 | 0.9982 |
| 0.0 | 40.0 | 27680 | 0.0163 | 0.9982 |
| 0.0 | 41.0 | 28372 | 0.0168 | 0.9982 |
| 0.0 | 42.0 | 29064 | 0.0167 | 0.9982 |
| 0.0 | 43.0 | 29756 | 0.0167 | 0.9982 |
| 0.0 | 44.0 | 30448 | 0.0168 | 0.9982 |
| 0.0 | 45.0 | 31140 | 0.0168 | 0.9982 |
| 0.0 | 46.0 | 31832 | 0.0168 | 0.9982 |
| 0.0 | 47.0 | 32524 | 0.0168 | 0.9982 |
| 0.0 | 48.0 | 33216 | 0.0168 | 0.9982 |
| 0.0 | 49.0 | 33908 | 0.0169 | 0.9982 |
| 0.0 | 50.0 | 34600 | 0.0169 | 0.9982 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1
- Datasets 2.19.2
- Tokenizers 0.19.1
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