File size: 2,387 Bytes
0f5541b a7ead9e 0f5541b a7ead9e 0f5541b a7ead9e 0f5541b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_with_preprocessing_grid_search
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_with_preprocessing_grid_search
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8836
- Precision: 0.8262
- Recall: 0.8258
- F1: 0.8249
- Accuracy: 0.8724
## 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: 3e-05
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.047 | 1.0 | 510 | 0.6171 | 0.7493 | 0.8057 | 0.7716 | 0.8336 |
| 0.4348 | 2.0 | 1020 | 0.4954 | 0.8056 | 0.8646 | 0.8296 | 0.8714 |
| 0.2818 | 3.0 | 1530 | 0.6252 | 0.8181 | 0.8323 | 0.8212 | 0.8660 |
| 0.1793 | 4.0 | 2040 | 0.7381 | 0.8216 | 0.8258 | 0.8227 | 0.8733 |
| 0.1356 | 5.0 | 2550 | 0.8601 | 0.8161 | 0.8219 | 0.8165 | 0.8660 |
| 0.1023 | 6.0 | 3060 | 0.8526 | 0.8363 | 0.8299 | 0.8307 | 0.8758 |
| 0.0944 | 7.0 | 3570 | 0.8459 | 0.8234 | 0.8298 | 0.8251 | 0.8729 |
| 0.0631 | 8.0 | 4080 | 0.8519 | 0.8212 | 0.8325 | 0.8252 | 0.8714 |
| 0.0602 | 9.0 | 4590 | 0.8756 | 0.8200 | 0.8267 | 0.8226 | 0.8719 |
| 0.0532 | 10.0 | 5100 | 0.8836 | 0.8262 | 0.8258 | 0.8249 | 0.8724 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|