---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: output
  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. -->

# output

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2749
- Accuracy: 0.9364

## 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: 0.0005
- 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: cosine
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2399        | 1.0   | 2500  | 0.2539          | 0.9037   |
| 0.2454        | 2.0   | 5000  | 0.2753          | 0.9064   |
| 0.2251        | 3.0   | 7500  | 0.2436          | 0.9167   |
| 0.1996        | 4.0   | 10000 | 0.2271          | 0.9246   |
| 0.1845        | 5.0   | 12500 | 0.2116          | 0.9269   |
| 0.205         | 6.0   | 15000 | 0.1946          | 0.9312   |
| 0.1352        | 7.0   | 17500 | 0.2233          | 0.9328   |
| 0.1306        | 8.0   | 20000 | 0.2257          | 0.936    |
| 0.0849        | 9.0   | 22500 | 0.2582          | 0.9372   |
| 0.0609        | 10.0  | 25000 | 0.2749          | 0.9364   |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3