---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: MM-MM03
  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. -->

# MM-MM03

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: 0.6872
- Accuracy: 0.57
- F1: 0.5203

## 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: 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   | 0.6915          | 0.53     | 0.3672 |
| No log        | 0.01  | 100  | 0.6923          | 0.53     | 0.3672 |
| No log        | 0.01  | 150  | 0.6919          | 0.53     | 0.3672 |
| No log        | 0.01  | 200  | 0.6923          | 0.54     | 0.4195 |
| No log        | 0.02  | 250  | 0.6924          | 0.6      | 0.5777 |
| No log        | 0.02  | 300  | 0.6908          | 0.54     | 0.3892 |
| No log        | 0.03  | 350  | 0.6893          | 0.55     | 0.4104 |
| No log        | 0.03  | 400  | 0.6911          | 0.57     | 0.5437 |
| No log        | 0.03  | 450  | 0.6904          | 0.57     | 0.5482 |
| 0.6938        | 0.04  | 500  | 0.6981          | 0.47     | 0.3005 |
| 0.6938        | 0.04  | 550  | 0.6953          | 0.47     | 0.3005 |
| 0.6938        | 0.04  | 600  | 0.6891          | 0.56     | 0.5252 |
| 0.6938        | 0.05  | 650  | 0.6871          | 0.55     | 0.4817 |
| 0.6938        | 0.05  | 700  | 0.6898          | 0.56     | 0.4975 |
| 0.6938        | 0.06  | 750  | 0.6899          | 0.55     | 0.4817 |
| 0.6938        | 0.06  | 800  | 0.6906          | 0.51     | 0.5102 |
| 0.6938        | 0.06  | 850  | 0.6934          | 0.48     | 0.48   |
| 0.6938        | 0.07  | 900  | 0.6889          | 0.55     | 0.4817 |
| 0.6938        | 0.07  | 950  | 0.6996          | 0.47     | 0.3175 |
| 0.6929        | 0.07  | 1000 | 0.6894          | 0.59     | 0.5601 |
| 0.6929        | 0.08  | 1050 | 0.6941          | 0.5      | 0.4777 |
| 0.6929        | 0.08  | 1100 | 0.6927          | 0.49     | 0.4896 |
| 0.6929        | 0.08  | 1150 | 0.6916          | 0.49     | 0.4903 |
| 0.6929        | 0.09  | 1200 | 0.6874          | 0.56     | 0.5252 |
| 0.6929        | 0.09  | 1250 | 0.6872          | 0.57     | 0.5203 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0