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---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: intent_classfication
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. -->
# intent_classfication
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: 0.1313
- Accuracy: 0.9622
## 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: 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.647 | 1.0 | 655 | 1.0548 | 0.8502 |
| 1.0688 | 2.0 | 1310 | 0.5307 | 0.8945 |
| 0.683 | 3.0 | 1965 | 0.3331 | 0.9255 |
| 0.3873 | 4.0 | 2620 | 0.2548 | 0.9396 |
| 0.326 | 5.0 | 3275 | 0.2134 | 0.9480 |
| 0.29 | 6.0 | 3930 | 0.1842 | 0.9538 |
| 0.2409 | 7.0 | 4585 | 0.1675 | 0.9553 |
| 0.2292 | 8.0 | 5240 | 0.1594 | 0.9576 |
| 0.2217 | 9.0 | 5895 | 0.1492 | 0.9595 |
| 0.2029 | 10.0 | 6550 | 0.1433 | 0.9595 |
| 0.2036 | 11.0 | 7205 | 0.1369 | 0.9614 |
| 0.1865 | 12.0 | 7860 | 0.1347 | 0.9614 |
| 0.1899 | 13.0 | 8515 | 0.1327 | 0.9622 |
| 0.182 | 14.0 | 9170 | 0.1315 | 0.9622 |
| 0.181 | 15.0 | 9825 | 0.1313 | 0.9622 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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