---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: assignment2_meher_test3
  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_test3

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: 0.5370
- Precision: 0.1642
- Recall: 0.4158
- F1: 0.2354
- Accuracy: 0.8892

## 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   | 149  | 0.3231          | 0.1406    | 0.2405 | 0.1774 | 0.9098   |
| No log        | 2.0   | 298  | 0.2897          | 0.1711    | 0.3505 | 0.2300 | 0.9103   |
| No log        | 3.0   | 447  | 0.3376          | 0.1715    | 0.3849 | 0.2373 | 0.9029   |
| 0.3658        | 4.0   | 596  | 0.3870          | 0.1669    | 0.4261 | 0.2398 | 0.8887   |
| 0.3658        | 5.0   | 745  | 0.4245          | 0.1542    | 0.3952 | 0.2218 | 0.8884   |
| 0.3658        | 6.0   | 894  | 0.4291          | 0.1815    | 0.3986 | 0.2495 | 0.9024   |
| 0.0735        | 7.0   | 1043 | 0.5257          | 0.1530    | 0.4296 | 0.2256 | 0.8820   |
| 0.0735        | 8.0   | 1192 | 0.5211          | 0.1680    | 0.4261 | 0.2410 | 0.8900   |
| 0.0735        | 9.0   | 1341 | 0.5810          | 0.1560    | 0.4502 | 0.2317 | 0.8784   |
| 0.0735        | 10.0  | 1490 | 0.5370          | 0.1642    | 0.4158 | 0.2354 | 0.8892   |


### Framework versions

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