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

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: 0.3184
- 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: 3e-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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.0   | 50   | 0.6884          | 0.58     | 0.4258 |
| No log        | 0.01  | 100  | 0.6988          | 0.42     | 0.2485 |
| No log        | 0.01  | 150  | 0.6952          | 0.42     | 0.2485 |
| No log        | 0.02  | 200  | 0.6886          | 0.58     | 0.4258 |
| No log        | 0.02  | 250  | 0.6889          | 0.59     | 0.4481 |
| No log        | 0.02  | 300  | 0.6920          | 0.59     | 0.5916 |
| No log        | 0.03  | 350  | 0.6917          | 0.57     | 0.5535 |
| No log        | 0.03  | 400  | 0.6947          | 0.45     | 0.3250 |
| No log        | 0.04  | 450  | 0.6541          | 0.69     | 0.6866 |
| 0.6877        | 0.04  | 500  | 0.6117          | 0.7      | 0.6829 |
| 0.6877        | 0.04  | 550  | 0.5938          | 0.71     | 0.7030 |
| 0.6877        | 0.05  | 600  | 0.5851          | 0.74     | 0.7390 |
| 0.6877        | 0.05  | 650  | 0.5721          | 0.77     | 0.7645 |
| 0.6877        | 0.06  | 700  | 0.5612          | 0.77     | 0.7704 |
| 0.6877        | 0.06  | 750  | 0.5368          | 0.76     | 0.7612 |
| 0.6877        | 0.06  | 800  | 0.5013          | 0.77     | 0.7696 |
| 0.6877        | 0.07  | 850  | 0.4831          | 0.78     | 0.7792 |
| 0.6877        | 0.07  | 900  | 0.4831          | 0.78     | 0.7792 |
| 0.6877        | 0.08  | 950  | 0.4573          | 0.8      | 0.7886 |
| 0.5813        | 0.08  | 1000 | 0.4576          | 0.79     | 0.7792 |
| 0.5813        | 0.08  | 1050 | 0.4483          | 0.81     | 0.7956 |
| 0.5813        | 0.09  | 1100 | 0.4377          | 0.8      | 0.7886 |
| 0.5813        | 0.09  | 1150 | 0.4297          | 0.81     | 0.7956 |
| 0.5813        | 0.1   | 1200 | 0.4287          | 0.81     | 0.7956 |
| 0.5813        | 0.1   | 1250 | 0.4301          | 0.81     | 0.7956 |
| 0.5813        | 0.1   | 1300 | 0.4286          | 0.81     | 0.7956 |
| 0.5813        | 0.11  | 1350 | 0.4193          | 0.81     | 0.7956 |
| 0.5813        | 0.11  | 1400 | 0.4088          | 0.81     | 0.7956 |
| 0.5813        | 0.12  | 1450 | 0.4107          | 0.81     | 0.7956 |
| 0.4699        | 0.12  | 1500 | 0.4016          | 0.81     | 0.7956 |
| 0.4699        | 0.12  | 1550 | 0.4056          | 0.81     | 0.7956 |
| 0.4699        | 0.13  | 1600 | 0.4095          | 0.81     | 0.7956 |
| 0.4699        | 0.13  | 1650 | 0.3973          | 0.81     | 0.7956 |
| 0.4699        | 0.14  | 1700 | 0.3907          | 0.81     | 0.7956 |
| 0.4699        | 0.14  | 1750 | 0.3907          | 0.81     | 0.7956 |


### Framework versions

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