---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: assignment2_meher_test2
  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_meher_test2

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: 0.5440
- Precision: 0.2070
- Recall: 0.2440
- F1: 0.2240
- Accuracy: 0.9244

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 347  | 0.2833          | 0.1672    | 0.1787 | 0.1728 | 0.9252   |
| 0.2912        | 2.0   | 694  | 0.3104          | 0.1923    | 0.2062 | 0.1990 | 0.9262   |
| 0.1166        | 3.0   | 1041 | 0.3258          | 0.1973    | 0.2474 | 0.2195 | 0.9235   |
| 0.1166        | 4.0   | 1388 | 0.3608          | 0.1818    | 0.3024 | 0.2271 | 0.9131   |
| 0.054         | 5.0   | 1735 | 0.4753          | 0.2093    | 0.2165 | 0.2128 | 0.9239   |
| 0.0277        | 6.0   | 2082 | 0.4959          | 0.2181    | 0.2405 | 0.2288 | 0.9246   |
| 0.0277        | 7.0   | 2429 | 0.5534          | 0.2331    | 0.1890 | 0.2087 | 0.9309   |
| 0.0159        | 8.0   | 2776 | 0.5215          | 0.2281    | 0.2509 | 0.2390 | 0.9254   |
| 0.0091        | 9.0   | 3123 | 0.5522          | 0.2244    | 0.2405 | 0.2322 | 0.9256   |
| 0.0091        | 10.0  | 3470 | 0.5440          | 0.2070    | 0.2440 | 0.2240 | 0.9244   |


### Framework versions

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