Hugging Face's logo

zwellington
/
azahead-longformer-v1.0

Text Classification
Transformers
PyTorch
longformer
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
azahead-longformer-v1.0
File size: 2,134 Bytes 
e91e773
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
 
---
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
datasets:
- azaheadhealth
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: azahead-longformer-v1.0
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: azaheadhealth
      type: azaheadhealth
      config: small
      split: test
      args: small
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7916666666666666
    - name: F1
      type: f1
      value: 0.6666666666666666
    - name: Precision
      type: precision
      value: 0.625
    - name: Recall
      type: recall
      value: 0.7142857142857143
---

<!-- 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. -->

# azahead-longformer-v1.0

This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the azaheadhealth dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6326
- Accuracy: 0.7917
- F1: 0.6667
- Precision: 0.625
- Recall: 0.7143

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6853        | 1.0   | 20   | 0.6326          | 0.7917   | 0.6667 | 0.625     | 0.7143 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.2.1+cu121
- Datasets 2.16.1
- Tokenizers 0.13.2