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---
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
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