---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-nsp-20000-1e-06-16
  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-uncased-nsp-20000-1e-06-16

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3012

## 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-06
- train_batch_size: 64
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6973        | 1.0   | 313  | 0.6904          |
| 0.687         | 2.0   | 626  | 0.6692          |
| 0.6658        | 3.0   | 939  | 0.6267          |
| 0.6144        | 4.0   | 1252 | 0.5866          |
| 0.5881        | 5.0   | 1565 | 0.5340          |
| 0.5088        | 6.0   | 1878 | 0.4598          |
| 0.4688        | 7.0   | 2191 | 0.4126          |
| 0.4017        | 8.0   | 2504 | 0.3876          |
| 0.3672        | 9.0   | 2817 | 0.3703          |
| 0.3486        | 10.0  | 3130 | 0.3538          |
| 0.3225        | 11.0  | 3443 | 0.3447          |
| 0.3127        | 12.0  | 3756 | 0.3358          |
| 0.296         | 13.0  | 4069 | 0.3289          |
| 0.2868        | 14.0  | 4382 | 0.3220          |
| 0.277         | 15.0  | 4695 | 0.3196          |
| 0.2635        | 16.0  | 5008 | 0.3187          |
| 0.2599        | 17.0  | 5321 | 0.3125          |
| 0.2476        | 18.0  | 5634 | 0.3085          |
| 0.2501        | 19.0  | 5947 | 0.3085          |
| 0.2443        | 20.0  | 6260 | 0.3068          |
| 0.2415        | 21.0  | 6573 | 0.3039          |
| 0.227         | 22.0  | 6886 | 0.3048          |
| 0.2243        | 23.0  | 7199 | 0.3024          |
| 0.2209        | 24.0  | 7512 | 0.3028          |
| 0.2209        | 25.0  | 7825 | 0.3021          |
| 0.2173        | 26.0  | 8138 | 0.3037          |
| 0.2185        | 27.0  | 8451 | 0.3020          |
| 0.2198        | 28.0  | 8764 | 0.3013          |
| 0.2134        | 29.0  | 9077 | 0.3012          |
| 0.2088        | 30.0  | 9390 | 0.3014          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1