File size: 2,834 Bytes
09ace06
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
94
95
---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- bigbench
metrics:
- accuracy
model-index:
- name: bigbench_entailedpolarity-gpt2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: bigbench
      type: bigbench
      config: entailed_polarity
      split: train
      args: entailed_polarity
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9166666666666666
---

<!-- 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. -->

# bigbench_entailedpolarity-gpt2

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the bigbench dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0213
- Accuracy: 0.9167

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 24   | 0.5201          | 0.875    |
| No log        | 2.0   | 48   | 0.3512          | 0.875    |
| No log        | 3.0   | 72   | 0.4245          | 0.8333   |
| No log        | 4.0   | 96   | 0.3220          | 0.9167   |
| No log        | 5.0   | 120  | 0.3962          | 0.875    |
| No log        | 6.0   | 144  | 0.5551          | 0.875    |
| No log        | 7.0   | 168  | 0.8597          | 0.875    |
| No log        | 8.0   | 192  | 0.4610          | 0.9583   |
| No log        | 9.0   | 216  | 0.9003          | 0.9167   |
| No log        | 10.0  | 240  | 0.8778          | 0.9167   |
| No log        | 11.0  | 264  | 0.9036          | 0.9167   |
| No log        | 12.0  | 288  | 0.9188          | 0.9167   |
| No log        | 13.0  | 312  | 1.0192          | 0.9167   |
| No log        | 14.0  | 336  | 0.9984          | 0.9167   |
| No log        | 15.0  | 360  | 0.9718          | 0.9167   |
| No log        | 16.0  | 384  | 0.9882          | 0.9167   |
| No log        | 17.0  | 408  | 1.0189          | 0.9167   |
| No log        | 18.0  | 432  | 1.0210          | 0.9167   |
| No log        | 19.0  | 456  | 1.0211          | 0.9167   |
| No log        | 20.0  | 480  | 1.0213          | 0.9167   |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.10.1+cu102
- Datasets 2.15.0
- Tokenizers 0.15.0