|
--- |
|
license: mit |
|
base_model: microsoft/biogpt |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: MLMA_biogpt_tuned_1412 |
|
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. --> |
|
|
|
# MLMA_biogpt_tuned_1412 |
|
|
|
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1569 |
|
- Precision: 0.4752 |
|
- Recall: 0.5541 |
|
- F1: 0.5116 |
|
- Accuracy: 0.9544 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- 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 | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| 0.3317 | 1.0 | 679 | 0.1753 | 0.3832 | 0.4923 | 0.4309 | 0.9436 | |
|
| 0.1765 | 2.0 | 1358 | 0.1625 | 0.4394 | 0.5531 | 0.4897 | 0.9496 | |
|
| 0.1057 | 3.0 | 2037 | 0.1569 | 0.4752 | 0.5541 | 0.5116 | 0.9544 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
