---
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: 0.5007
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|
| 0.6651        | 0.2857 | 1    | 0.6412          | 0.9003   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 0.5714 | 2    | 0.6363          | 0.9239   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 0.8571 | 3    | 0.6264          | 0.9475   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 1.1429 | 4    | 0.6125          | 0.9606   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 1.4286 | 5    | 0.5944          | 0.9685   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 1.7143 | 6    | 0.5722          | 0.9738   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 2.0    | 7    | 0.5467          | 0.9790   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 2.2857 | 8    | 0.5230          | 0.9816   | 0.0 | 0.0       | 0.0    |
| 0.6651        | 2.5714 | 9    | 0.5007          | 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