File size: 1,760 Bytes
4b0011a
 
cf6d611
4b0011a
 
 
 
 
 
 
 
 
 
 
 
 
 
cf6d611
 
 
 
4b0011a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
cf6d611
 
 
4b0011a
 
 
 
cf6d611
4b0011a
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
---
license: mit
base_model: facebook/esm2_t12_35M_UR50D
tags:
- generated_from_keras_callback
model-index:
- name: esm2_t12_35M_UR50D-finetuned-cytosol-membrane-classification
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# esm2_t12_35M_UR50D-finetuned-cytosol-membrane-classification

This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0918
- Train Accuracy: 0.9694
- Validation Loss: 0.1640
- Validation Accuracy: 0.9495
- Epoch: 2

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.0}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.2427     | 0.9271         | 0.1663          | 0.9464              | 0     |
| 0.1468     | 0.9538         | 0.1505          | 0.9495              | 1     |
| 0.0918     | 0.9694         | 0.1640          | 0.9495              | 2     |


### Framework versions

- Transformers 4.40.1
- TensorFlow 2.15.0
- Datasets 2.19.0
- Tokenizers 0.19.1