bert-base-uncased / README.md
Shiko07's picture
End of training
e6875b0
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased
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
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: 0.7672
- Rmse: 0.6779
## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7744 | 0.5 | 500 | 0.7366 | 0.7180 |
| 0.7071 | 1.0 | 1000 | 0.6900 | 0.7068 |
| 0.5951 | 1.5 | 1500 | 0.6372 | 0.6764 |
| 0.5814 | 2.0 | 2000 | 0.6076 | 0.6986 |
| 0.4345 | 2.5 | 2500 | 0.7680 | 0.6793 |
| 0.404 | 3.0 | 3000 | 0.7672 | 0.6779 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1