---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-cased-massive_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-base-cased-massive_intent

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5797
- Accuracy: 0.8716

## 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: 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.3465        | 1.0   | 720   | 2.3843          | 0.5347   |
| 1.9972        | 2.0   | 1440  | 1.4809          | 0.7093   |
| 1.3555        | 3.0   | 2160  | 1.0981          | 0.7757   |
| 1.0033        | 4.0   | 2880  | 0.8683          | 0.8259   |
| 0.7694        | 5.0   | 3600  | 0.7548          | 0.8387   |
| 0.613         | 6.0   | 4320  | 0.6804          | 0.8480   |
| 0.5019        | 7.0   | 5040  | 0.6344          | 0.8544   |
| 0.4203        | 8.0   | 5760  | 0.6095          | 0.8633   |
| 0.3599        | 9.0   | 6480  | 0.5934          | 0.8633   |
| 0.3099        | 10.0  | 7200  | 0.5879          | 0.8623   |
| 0.2783        | 11.0  | 7920  | 0.5834          | 0.8682   |
| 0.2499        | 12.0  | 8640  | 0.5825          | 0.8642   |
| 0.2292        | 13.0  | 9360  | 0.5813          | 0.8677   |
| 0.2164        | 14.0  | 10080 | 0.5797          | 0.8716   |
| 0.2104        | 15.0  | 10800 | 0.5816          | 0.8677   |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1