---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: assignment2_attempt12
  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. -->

# assignment2_attempt12

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: 0.4465
- Precision: 0.2230
- Recall: 0.2268
- F1: 0.2249
- Accuracy: 0.9262

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 347  | 0.2699          | 0.1554    | 0.1581 | 0.1567 | 0.9238   |
| 0.3071        | 2.0   | 694  | 0.3111          | 0.1843    | 0.1375 | 0.1575 | 0.9302   |
| 0.1235        | 3.0   | 1041 | 0.3048          | 0.2164    | 0.2543 | 0.2338 | 0.9280   |
| 0.1235        | 4.0   | 1388 | 0.3606          | 0.1920    | 0.2302 | 0.2094 | 0.9208   |
| 0.0592        | 5.0   | 1735 | 0.4584          | 0.2112    | 0.1684 | 0.1874 | 0.9280   |
| 0.0304        | 6.0   | 2082 | 0.4465          | 0.2230    | 0.2268 | 0.2249 | 0.9262   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1