---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: bert-base-cased
model-index:
- name: bert-finetuned-comp2
  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-finetuned-comp2

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: 0.9570
- Precision: 0.5169
- Recall: 0.6765
- F1: 0.5820
- Accuracy: 0.5820

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.8434        | 1.0   | 934  | 0.7147          | 0.4475    | 0.6252 | 0.5096 | 0.5096   |
| 0.6307        | 2.0   | 1868 | 0.5959          | 0.5058    | 0.6536 | 0.5585 | 0.5585   |
| 0.4691        | 3.0   | 2802 | 0.6555          | 0.4761    | 0.6865 | 0.5521 | 0.5521   |
| 0.334         | 4.0   | 3736 | 0.7211          | 0.5292    | 0.6682 | 0.5863 | 0.5863   |
| 0.2326        | 5.0   | 4670 | 0.8046          | 0.4886    | 0.6865 | 0.5682 | 0.5682   |
| 0.1625        | 6.0   | 5604 | 0.8650          | 0.4972    | 0.6851 | 0.5728 | 0.5728   |
| 0.1195        | 7.0   | 6538 | 0.9570          | 0.5169    | 0.6765 | 0.5820 | 0.5820   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6