File size: 1,891 Bytes
1344908
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: ro-sequence
  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. -->

# ro-sequence

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 815.9874
- Precision: 0.7802
- Recall: 0.8225
- F1: 0.8008

## 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: 4e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 352269
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 798.342       | 1.0   | 125  | 619.5866        | 0.7472    | 0.7369 | 0.7420 |
| 377.8265      | 2.0   | 250  | 521.1552        | 0.7833    | 0.7998 | 0.7915 |
| 288.2568      | 3.0   | 375  | 559.4092        | 0.7469    | 0.8145 | 0.7792 |
| 192.2052      | 4.0   | 500  | 555.9223        | 0.8252    | 0.7889 | 0.8066 |
| 128.4364      | 5.0   | 625  | 719.3274        | 0.7848    | 0.8042 | 0.7944 |
| 86.742        | 6.0   | 750  | 797.8254        | 0.7391    | 0.8281 | 0.7811 |
| 62.8087       | 7.0   | 875  | 815.9874        | 0.7802    | 0.8225 | 0.8008 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1