File size: 2,751 Bytes
0ceb58c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: t_5_classifier
  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. -->

# t_5_classifier

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5350
- F1: 0.7367
- Accuracy: 0.7299

## 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: 128
- eval_batch_size: 128
- 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 | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| No log        | 1.0   | 49   | 0.6857          | 0.6233 | 0.4126   |
| No log        | 2.0   | 98   | 0.6695          | 0.6567 | 0.5429   |
| No log        | 3.0   | 147  | 0.6445          | 0.6898 | 0.6202   |
| No log        | 4.0   | 196  | 0.6087          | 0.7053 | 0.6680   |
| No log        | 5.0   | 245  | 0.5762          | 0.7122 | 0.6944   |
| No log        | 6.0   | 294  | 0.5601          | 0.7180 | 0.7054   |
| No log        | 7.0   | 343  | 0.5512          | 0.7281 | 0.7189   |
| No log        | 8.0   | 392  | 0.5471          | 0.7303 | 0.7189   |
| No log        | 9.0   | 441  | 0.5457          | 0.7311 | 0.7195   |
| No log        | 10.0  | 490  | 0.5405          | 0.7315 | 0.7234   |
| 0.607         | 11.0  | 539  | 0.5386          | 0.7319 | 0.7234   |
| 0.607         | 12.0  | 588  | 0.5391          | 0.7321 | 0.7240   |
| 0.607         | 13.0  | 637  | 0.5378          | 0.7357 | 0.7286   |
| 0.607         | 14.0  | 686  | 0.5362          | 0.7368 | 0.7305   |
| 0.607         | 15.0  | 735  | 0.5352          | 0.7392 | 0.7324   |
| 0.607         | 16.0  | 784  | 0.5360          | 0.7344 | 0.7292   |
| 0.607         | 17.0  | 833  | 0.5360          | 0.7358 | 0.7292   |
| 0.607         | 18.0  | 882  | 0.5353          | 0.7359 | 0.7305   |
| 0.607         | 19.0  | 931  | 0.5351          | 0.7374 | 0.7305   |
| 0.607         | 20.0  | 980  | 0.5350          | 0.7367 | 0.7299   |


### Framework versions

- Transformers 4.41.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1