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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- accuracy
- f1
model-index:
- name: Bert_Test
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_Test
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1965
- Precision: 0.9332
- Accuracy: 0.9223
- F1: 0.9223
## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:--------:|:------:|
| 0.6717 | 0.4 | 500 | 0.6049 | 0.7711 | 0.6743 | 0.6112 |
| 0.5704 | 0.8 | 1000 | 0.5299 | 0.7664 | 0.7187 | 0.6964 |
| 0.52 | 1.2 | 1500 | 0.4866 | 0.7698 | 0.7537 | 0.7503 |
| 0.4792 | 1.6 | 2000 | 0.4292 | 0.8031 | 0.793 | 0.7927 |
| 0.4332 | 2.0 | 2500 | 0.3920 | 0.8318 | 0.8203 | 0.8198 |
| 0.381 | 2.4 | 3000 | 0.3723 | 0.9023 | 0.8267 | 0.8113 |
| 0.3625 | 2.8 | 3500 | 0.3134 | 0.8736 | 0.8607 | 0.8601 |
| 0.3325 | 3.2 | 4000 | 0.2924 | 0.8973 | 0.871 | 0.8683 |
| 0.3069 | 3.6 | 4500 | 0.2671 | 0.8916 | 0.8847 | 0.8851 |
| 0.2866 | 4.0 | 5000 | 0.2571 | 0.8920 | 0.8913 | 0.8926 |
| 0.2595 | 4.4 | 5500 | 0.2450 | 0.8980 | 0.9 | 0.9015 |
| 0.2567 | 4.8 | 6000 | 0.2246 | 0.9057 | 0.9043 | 0.9054 |
| 0.2255 | 5.2 | 6500 | 0.2263 | 0.9332 | 0.905 | 0.9030 |
| 0.2237 | 5.6 | 7000 | 0.2083 | 0.9265 | 0.9157 | 0.9156 |
| 0.2248 | 6.0 | 7500 | 0.2039 | 0.9387 | 0.9193 | 0.9185 |
| 0.2086 | 6.4 | 8000 | 0.2038 | 0.9436 | 0.9193 | 0.9181 |
| 0.2029 | 6.8 | 8500 | 0.1965 | 0.9332 | 0.9223 | 0.9223 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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