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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bertBasev2
  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. -->

# bertBasev2

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0328
- Precision: 0.9539
- Recall: 0.9707
- F1: 0.9622
- Accuracy: 0.9911

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.2004        | 1.0   | 1012 | 0.9504          | 0.2620    | 0.3519 | 0.3004 | 0.6856   |
| 1.0265        | 2.0   | 2024 | 0.6205          | 0.4356    | 0.5161 | 0.4725 | 0.7956   |
| 0.6895        | 3.0   | 3036 | 0.3269          | 0.6694    | 0.7302 | 0.6985 | 0.9044   |
| 0.44          | 4.0   | 4048 | 0.1325          | 0.8356    | 0.9091 | 0.8708 | 0.9667   |
| 0.2585        | 5.0   | 5060 | 0.0717          | 0.9259    | 0.9531 | 0.9393 | 0.9844   |
| 0.1722        | 6.0   | 6072 | 0.0382          | 0.9480    | 0.9619 | 0.9549 | 0.99     |
| 0.0919        | 7.0   | 7084 | 0.0328          | 0.9539    | 0.9707 | 0.9622 | 0.9911   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
