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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
|