update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,76 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
tags:
|
| 3 |
+
- generated_from_trainer
|
| 4 |
+
metrics:
|
| 5 |
+
- accuracy
|
| 6 |
+
- f1
|
| 7 |
+
- precision
|
| 8 |
+
- recall
|
| 9 |
+
model-index:
|
| 10 |
+
- name: ESM1b_AAV2_classification
|
| 11 |
+
results: []
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
+
|
| 17 |
+
# ESM1b_AAV2_classification
|
| 18 |
+
|
| 19 |
+
This model is a fine-tuned version of [facebook/esm-1b](https://huggingface.co/facebook/esm-1b) on an unknown dataset.
|
| 20 |
+
It achieves the following results on the evaluation set:
|
| 21 |
+
- Loss: 0.2250
|
| 22 |
+
- Accuracy: 0.9620
|
| 23 |
+
- F1: 0.9632
|
| 24 |
+
- Precision: 0.9642
|
| 25 |
+
- Recall: 0.9622
|
| 26 |
+
- Auroc: 0.9620
|
| 27 |
+
|
| 28 |
+
## Model description
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Intended uses & limitations
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training and evaluation data
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training procedure
|
| 41 |
+
|
| 42 |
+
### Training hyperparameters
|
| 43 |
+
|
| 44 |
+
The following hyperparameters were used during training:
|
| 45 |
+
- learning_rate: 5e-05
|
| 46 |
+
- train_batch_size: 16
|
| 47 |
+
- eval_batch_size: 32
|
| 48 |
+
- seed: 42
|
| 49 |
+
- gradient_accumulation_steps: 64
|
| 50 |
+
- total_train_batch_size: 1024
|
| 51 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 52 |
+
- lr_scheduler_type: linear
|
| 53 |
+
- lr_scheduler_warmup_steps: 200
|
| 54 |
+
- num_epochs: 8
|
| 55 |
+
- mixed_precision_training: Native AMP
|
| 56 |
+
|
| 57 |
+
### Training results
|
| 58 |
+
|
| 59 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Auroc |
|
| 60 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
|
| 61 |
+
| No log | 1.0 | 232 | 0.1311 | 0.9495 | 0.9501 | 0.9711 | 0.9299 | 0.9502 |
|
| 62 |
+
| No log | 2.0 | 464 | 0.1032 | 0.9606 | 0.9620 | 0.9583 | 0.9657 | 0.9604 |
|
| 63 |
+
| 0.1924 | 3.0 | 696 | 0.0995 | 0.9627 | 0.9641 | 0.9584 | 0.9700 | 0.9625 |
|
| 64 |
+
| 0.1924 | 4.0 | 928 | 0.1218 | 0.9611 | 0.9624 | 0.9607 | 0.9641 | 0.9610 |
|
| 65 |
+
| 0.067 | 5.0 | 1160 | 0.1187 | 0.9622 | 0.9633 | 0.9678 | 0.9588 | 0.9623 |
|
| 66 |
+
| 0.067 | 6.0 | 1392 | 0.1514 | 0.9612 | 0.9621 | 0.9710 | 0.9534 | 0.9615 |
|
| 67 |
+
| 0.0271 | 7.0 | 1624 | 0.1890 | 0.9612 | 0.9626 | 0.9580 | 0.9673 | 0.9610 |
|
| 68 |
+
| 0.0271 | 8.0 | 1856 | 0.2250 | 0.9620 | 0.9632 | 0.9642 | 0.9622 | 0.9620 |
|
| 69 |
+
|
| 70 |
+
|
| 71 |
+
### Framework versions
|
| 72 |
+
|
| 73 |
+
- Transformers 4.13.0.dev0
|
| 74 |
+
- Pytorch 1.11.0+cu113
|
| 75 |
+
- Datasets 2.1.0
|
| 76 |
+
- Tokenizers 0.10.3
|