---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: MM05-PC
  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. -->

# MM05-PC

This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3358
- Accuracy: 0.99
- F1: 0.9950

## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.0   | 50   | 0.6889          | 0.58     | 0.4258 |
| No log        | 0.01  | 100  | 0.6984          | 0.42     | 0.2485 |
| No log        | 0.01  | 150  | 0.6948          | 0.42     | 0.2485 |
| No log        | 0.02  | 200  | 0.6867          | 0.58     | 0.4258 |
| No log        | 0.02  | 250  | 0.6859          | 0.75     | 0.7192 |
| No log        | 0.02  | 300  | 0.6674          | 0.67     | 0.6705 |
| No log        | 0.03  | 350  | 0.6093          | 0.65     | 0.6514 |
| No log        | 0.03  | 400  | 0.5726          | 0.71     | 0.7118 |
| No log        | 0.04  | 450  | 0.5586          | 0.73     | 0.7311 |
| 0.6576        | 0.04  | 500  | 0.5368          | 0.67     | 0.6680 |
| 0.6576        | 0.04  | 550  | 0.5532          | 0.73     | 0.7311 |
| 0.6576        | 0.05  | 600  | 0.5290          | 0.73     | 0.7311 |
| 0.6576        | 0.05  | 650  | 0.5073          | 0.73     | 0.7311 |
| 0.6576        | 0.06  | 700  | 0.4731          | 0.76     | 0.7489 |
| 0.6576        | 0.06  | 750  | 0.4519          | 0.81     | 0.7956 |
| 0.6576        | 0.06  | 800  | 0.4411          | 0.81     | 0.7956 |
| 0.6576        | 0.07  | 850  | 0.4401          | 0.81     | 0.7956 |
| 0.6576        | 0.07  | 900  | 0.4382          | 0.81     | 0.7956 |
| 0.6576        | 0.08  | 950  | 0.4351          | 0.81     | 0.7956 |
| 0.4885        | 0.08  | 1000 | 0.4348          | 0.81     | 0.7956 |
| 0.4885        | 0.08  | 1050 | 0.4289          | 0.81     | 0.7956 |
| 0.4885        | 0.09  | 1100 | 0.4130          | 0.81     | 0.7956 |
| 0.4885        | 0.09  | 1150 | 0.4087          | 0.81     | 0.7956 |
| 0.4885        | 0.1   | 1200 | 0.4165          | 0.81     | 0.7956 |
| 0.4885        | 0.1   | 1250 | 0.4088          | 0.81     | 0.7956 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0