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---
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 |