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---
license: mit
base_model: nlpie/bio-mobilebert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: NLPGroupProject-Finetune-bio-mobilebert
  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. -->

# NLPGroupProject-Finetune-bio-mobilebert

This model is a fine-tuned version of [nlpie/bio-mobilebert](https://huggingface.co/nlpie/bio-mobilebert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9925
- Accuracy: 0.737

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.25  | 250  | 0.8564          | 0.705    |
| 12.045        | 0.5   | 500  | 0.7663          | 0.726    |
| 12.045        | 0.75  | 750  | 0.7659          | 0.707    |
| 0.8388        | 1.0   | 1000 | 0.7144          | 0.737    |
| 0.8388        | 1.25  | 1250 | 0.7986          | 0.734    |
| 0.658         | 1.5   | 1500 | 0.8002          | 0.728    |
| 0.658         | 1.75  | 1750 | 0.7685          | 0.736    |
| 0.6945        | 2.0   | 2000 | 0.7751          | 0.738    |
| 0.6945        | 2.25  | 2250 | 1.2388          | 0.73     |
| 0.5058        | 2.5   | 2500 | 1.1562          | 0.733    |
| 0.5058        | 2.75  | 2750 | 0.9343          | 0.736    |
| 0.5251        | 3.0   | 3000 | 0.9925          | 0.737    |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1