---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: assignment2_attempt11
  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_attempt11

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: 0.6058
- Precision: 0.2642
- Recall: 0.1186
- F1: 0.1637
- Accuracy: 0.9370

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 128  | 0.3124          | 0.2308    | 0.0254 | 0.0458 | 0.9401   |
| No log        | 2.0   | 256  | 0.2862          | 0.1636    | 0.0763 | 0.1040 | 0.9353   |
| No log        | 3.0   | 384  | 0.3899          | 0.2093    | 0.0763 | 0.1118 | 0.9359   |
| 0.1996        | 4.0   | 512  | 0.4161          | 0.3095    | 0.1102 | 0.1625 | 0.9382   |
| 0.1996        | 5.0   | 640  | 0.4845          | 0.3077    | 0.1017 | 0.1529 | 0.9392   |
| 0.1996        | 6.0   | 768  | 0.4841          | 0.2692    | 0.1186 | 0.1647 | 0.9365   |
| 0.1996        | 7.0   | 896  | 0.4987          | 0.2258    | 0.1186 | 0.1556 | 0.9349   |
| 0.0254        | 8.0   | 1024 | 0.5512          | 0.2766    | 0.1102 | 0.1576 | 0.9370   |
| 0.0254        | 9.0   | 1152 | 0.5772          | 0.3171    | 0.1102 | 0.1635 | 0.9379   |
| 0.0254        | 10.0  | 1280 | 0.5764          | 0.2586    | 0.1271 | 0.1705 | 0.9342   |
| 0.0254        | 11.0  | 1408 | 0.5964          | 0.2917    | 0.1186 | 0.1687 | 0.9380   |
| 0.005         | 12.0  | 1536 | 0.5952          | 0.2642    | 0.1186 | 0.1637 | 0.9368   |
| 0.005         | 13.0  | 1664 | 0.5980          | 0.2593    | 0.1186 | 0.1628 | 0.9367   |
| 0.005         | 14.0  | 1792 | 0.6033          | 0.2642    | 0.1186 | 0.1637 | 0.9370   |
| 0.005         | 15.0  | 1920 | 0.6058          | 0.2642    | 0.1186 | 0.1637 | 0.9370   |


### Framework versions

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