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---
base_model: facebook/esm2_t6_8M_UR50D
library_name: peft
license: mit
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: esm2_t12_35M-lora-binding-sites_2024-07-02_09-26-54
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_t6_8M-lora-binding-sites_2024-07-02_09-26-54
This model is a fine-tuned version of [facebook/esm2_t6_8M_UR50D](https://huggingface.co/facebook/esm2_t6_8M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3706
- Accuracy: 0.8880
- Precision: 0.1563
- Recall: 0.7878
- F1: 0.2608
- Auc: 0.8392
- Mcc: 0.3192
## 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: 0.0005701568055793089
- train_batch_size: 12
- eval_batch_size: 12
- seed: 8893
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc | Mcc |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:------:|
| 0.2569 | 1.0 | 14485 | 0.3706 | 0.8880 | 0.1563 | 0.7878 | 0.2608 | 0.8392 | 0.3192 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |