---
library_name: transformers
license: other
base_model: DedalusHealthCare/tinybert-mlm-en
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: tinybert
  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. -->

# tinybert

This model is a fine-tuned version of [DedalusHealthCare/tinybert-mlm-en](https://huggingface.co/DedalusHealthCare/tinybert-mlm-en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5776
- Accuracy: 0.9816
- F1: 0.0
- Precision: 0.0
- Recall: 0.0

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7155        | 0.2857 | 1    | 0.7256          | 0.1969   | 0.0437 | 0.0224    | 1.0    |
| 0.7155        | 0.5714 | 2    | 0.7204          | 0.2283   | 0.0455 | 0.0233    | 1.0    |
| 0.7155        | 0.8571 | 3    | 0.7102          | 0.3333   | 0.0451 | 0.0232    | 0.8571 |
| 0.7155        | 1.1429 | 4    | 0.6954          | 0.4803   | 0.0388 | 0.0201    | 0.5714 |
| 0.7155        | 1.4286 | 5    | 0.6763          | 0.7008   | 0.0500 | 0.0265    | 0.4286 |
| 0.7155        | 1.7143 | 6    | 0.6533          | 0.8530   | 0.0345 | 0.0196    | 0.1429 |
| 0.7155        | 2.0    | 7    | 0.6268          | 0.9580   | 0.0    | 0.0       | 0.0    |
| 0.7155        | 2.2857 | 8    | 0.6016          | 0.9816   | 0.0    | 0.0       | 0.0    |
| 0.7155        | 2.5714 | 9    | 0.5776          | 0.9816   | 0.0    | 0.0       | 0.0    |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.6.0+cu124
- Datasets 2.16.0
- Tokenizers 0.20.3