|
--- |
|
license: mit |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: facebook/esm2_t36_3B_UR50D |
|
metrics: |
|
- precision |
|
- recall |
|
- accuracy |
|
model-index: |
|
- name: esm2-t36-3B-lora-16-remote-homology-filtered |
|
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. --> |
|
|
|
# esm2-t36-3B-lora-16-remote-homology-filtered |
|
|
|
This model is a fine-tuned version of [facebook/esm2_t36_3B_UR50D](https://huggingface.co/facebook/esm2_t36_3B_UR50D) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4403 |
|
- Precision: 0.7922 |
|
- Recall: 0.8139 |
|
- F1-score: 0.8029 |
|
- Accuracy: 0.7990 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 96 |
|
- eval_batch_size: 96 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 192 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:| |
|
| 0.535 | 0.9992 | 664 | 0.5186 | 0.8002 | 0.6630 | 0.7252 | 0.7472 | |
|
| 0.4946 | 2.0 | 1329 | 0.5065 | 0.6945 | 0.8969 | 0.7828 | 0.7496 | |
|
| 0.4727 | 2.9992 | 1993 | 0.4592 | 0.7917 | 0.7876 | 0.7897 | 0.7889 | |
|
| 0.4439 | 4.0 | 2658 | 0.4471 | 0.8087 | 0.7798 | 0.7940 | 0.7964 | |
|
| 0.4234 | 4.9962 | 3320 | 0.4403 | 0.7922 | 0.8139 | 0.8029 | 0.7990 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.10.0 |
|
- Transformers 4.40.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
