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---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/esm2_t12_35M_UR50D
metrics:
- precision
- recall
- accuracy
model-index:
- name: esm2-t12-35M-lora-64-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-t12-35M-lora-64-remote-homology-filtered
This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5657
- Precision: 0.7166
- Recall: 0.6986
- F1-score: 0.7075
- Accuracy: 0.7141
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.6191 | 1.0 | 7969 | 0.6185 | 0.6919 | 0.5824 | 0.6325 | 0.6650 |
| 0.5921 | 2.0 | 15938 | 0.5838 | 0.7201 | 0.6339 | 0.6742 | 0.6968 |
| 0.5874 | 3.0 | 23907 | 0.5751 | 0.7439 | 0.6104 | 0.6705 | 0.7032 |
| 0.5593 | 4.0 | 31876 | 0.5664 | 0.7210 | 0.6833 | 0.7016 | 0.7124 |
| 0.576 | 5.0 | 39845 | 0.5657 | 0.7166 | 0.6986 | 0.7075 | 0.7141 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2 |