---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: assignment2_attempt10
  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_attempt10

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: 0.5285
- Precision: 0.4333
- Recall: 0.1102
- F1: 0.1757
- Accuracy: 0.9417

## 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   | 128  | 0.3044          | 0.0       | 0.0    | 0.0    | 0.9385   |
| No log        | 2.0   | 256  | 0.2727          | 0.1341    | 0.0932 | 0.11   | 0.9370   |
| No log        | 3.0   | 384  | 0.3383          | 0.2973    | 0.0932 | 0.1419 | 0.9413   |
| 0.2087        | 4.0   | 512  | 0.3512          | 0.3171    | 0.1102 | 0.1635 | 0.9409   |
| 0.2087        | 5.0   | 640  | 0.3298          | 0.175     | 0.1186 | 0.1414 | 0.9383   |
| 0.2087        | 6.0   | 768  | 0.3793          | 0.2209    | 0.1610 | 0.1863 | 0.9363   |
| 0.2087        | 7.0   | 896  | 0.5285          | 0.4333    | 0.1102 | 0.1757 | 0.9417   |


### Framework versions

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