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---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nlpcw_bert-base-uncased-abbr
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. -->
# nlpcw_bert-base-uncased-abbr
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2675
- Precision: 0.9390
- Recall: 0.9349
- F1: 0.9369
- Accuracy: 0.9317
## 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: 2e-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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6325 | 1.0 | 67 | 0.2629 | 0.9036 | 0.9090 | 0.9063 | 0.9043 |
| 0.3169 | 2.0 | 134 | 0.2297 | 0.9309 | 0.9137 | 0.9223 | 0.9182 |
| 0.1994 | 3.0 | 201 | 0.2282 | 0.9310 | 0.9193 | 0.9251 | 0.9223 |
| 0.17 | 4.0 | 268 | 0.2193 | 0.9366 | 0.9286 | 0.9326 | 0.9278 |
| 0.1457 | 5.0 | 335 | 0.2350 | 0.9395 | 0.9373 | 0.9384 | 0.9331 |
| 0.1086 | 6.0 | 402 | 0.2435 | 0.9418 | 0.9340 | 0.9379 | 0.9331 |
| 0.0908 | 7.0 | 469 | 0.2537 | 0.9357 | 0.9283 | 0.9319 | 0.9270 |
| 0.0791 | 8.0 | 536 | 0.2675 | 0.9390 | 0.9349 | 0.9369 | 0.9317 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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