---
library_name: transformers
license: mit
base_model: prajjwal1/bert-mini
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: my_mind_classifier_BertMini
  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. -->

# my_mind_classifier_BertMini

This model is a fine-tuned version of [prajjwal1/bert-mini](https://huggingface.co/prajjwal1/bert-mini) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4530
- Accuracy: 0.8620
- Precision: 0.8578
- Recall: 0.8620
- F1: 0.8599

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6179        | 1.0   | 9024  | 0.5588          | 0.8303   | 0.8272    | 0.8303 | 0.8288 |
| 0.4973        | 2.0   | 18048 | 0.4530          | 0.8620   | 0.8578    | 0.8620 | 0.8599 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0