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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results_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. -->
# results_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: 0.1808
- Accuracy: 0.9261
- Precision: 0.9343
- Recall: 0.9443
- F1: 0.9393
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5507 | 0.09 | 50 | 0.3325 | 0.8642 | 0.9461 | 0.8224 | 0.8799 |
| 0.3193 | 0.18 | 100 | 0.3217 | 0.8701 | 0.9665 | 0.8135 | 0.8835 |
| 0.2726 | 0.28 | 150 | 0.2532 | 0.8918 | 0.9091 | 0.9125 | 0.9108 |
| 0.2143 | 0.37 | 200 | 0.2203 | 0.9146 | 0.9281 | 0.9310 | 0.9295 |
| 0.2134 | 0.46 | 250 | 0.2371 | 0.9162 | 0.9035 | 0.9645 | 0.9330 |
| 0.2234 | 0.55 | 300 | 0.2027 | 0.9178 | 0.9130 | 0.9552 | 0.9336 |
| 0.2139 | 0.64 | 350 | 0.1986 | 0.9194 | 0.9125 | 0.9587 | 0.9351 |
| 0.2062 | 0.74 | 400 | 0.1853 | 0.9222 | 0.9469 | 0.9232 | 0.9349 |
| 0.1793 | 0.83 | 450 | 0.1953 | 0.9244 | 0.9213 | 0.9567 | 0.9387 |
| 0.1771 | 0.92 | 500 | 0.1808 | 0.9261 | 0.9343 | 0.9443 | 0.9393 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
|