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---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-uncased_12112024T103207
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_12112024T103207
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4280
- F1: 0.8755
- Learning Rate: 0.0
## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 600
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Rate |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| No log | 0.9942 | 86 | 1.7552 | 0.1858 | 0.0000 |
| No log | 2.0 | 173 | 1.6269 | 0.3187 | 0.0000 |
| No log | 2.9942 | 259 | 1.4885 | 0.4438 | 0.0000 |
| No log | 4.0 | 346 | 1.3478 | 0.4980 | 0.0000 |
| No log | 4.9942 | 432 | 1.1903 | 0.5445 | 0.0000 |
| 1.5065 | 6.0 | 519 | 1.0219 | 0.5810 | 0.0000 |
| 1.5065 | 6.9942 | 605 | 0.9065 | 0.6140 | 1e-05 |
| 1.5065 | 8.0 | 692 | 0.7955 | 0.6526 | 0.0000 |
| 1.5065 | 8.9942 | 778 | 0.6876 | 0.7032 | 0.0000 |
| 1.5065 | 10.0 | 865 | 0.6171 | 0.7536 | 0.0000 |
| 1.5065 | 10.9942 | 951 | 0.5734 | 0.7612 | 0.0000 |
| 0.7171 | 12.0 | 1038 | 0.4960 | 0.8147 | 0.0000 |
| 0.7171 | 12.9942 | 1124 | 0.4820 | 0.8358 | 0.0000 |
| 0.7171 | 14.0 | 1211 | 0.4557 | 0.8445 | 0.0000 |
| 0.7171 | 14.9942 | 1297 | 0.4596 | 0.8524 | 0.0000 |
| 0.7171 | 16.0 | 1384 | 0.4299 | 0.8651 | 0.0000 |
| 0.7171 | 16.9942 | 1470 | 0.4426 | 0.8671 | 6e-06 |
| 0.2382 | 18.0 | 1557 | 0.4280 | 0.8755 | 0.0000 |
| 0.2382 | 18.9942 | 1643 | 0.4517 | 0.8728 | 0.0000 |
| 0.2382 | 20.0 | 1730 | 0.4473 | 0.8761 | 0.0000 |
| 0.2382 | 20.9942 | 1816 | 0.4599 | 0.8798 | 0.0000 |
| 0.2382 | 22.0 | 1903 | 0.4927 | 0.8777 | 0.0000 |
| 0.2382 | 22.9942 | 1989 | 0.4768 | 0.8819 | 0.0000 |
| 0.0713 | 24.0 | 2076 | 0.4970 | 0.8808 | 0.0000 |
| 0.0713 | 24.9942 | 2162 | 0.5031 | 0.8808 | 0.0000 |
| 0.0713 | 26.0 | 2249 | 0.4807 | 0.8845 | 7e-07 |
| 0.0713 | 26.9942 | 2335 | 0.4959 | 0.8825 | 4e-07 |
| 0.0713 | 28.0 | 2422 | 0.5034 | 0.8818 | 2e-07 |
| 0.0344 | 28.9942 | 2508 | 0.5037 | 0.8818 | 0.0 |
| 0.0344 | 29.8266 | 2580 | 0.5037 | 0.8824 | 0.0 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1
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