File size: 3,269 Bytes
d158c42 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: spellcorrector_3110_v17
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. -->
# spellcorrector_3110_v17
This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0086
- Precision: 0.9991
- Recall: 0.9990
- F1: 0.9990
- Accuracy: 0.9977
## 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: 4
- eval_batch_size: 4
- 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 | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1377 | 1.0 | 1949 | 0.1114 | 0.9542 | 0.9820 | 0.9679 | 0.9757 |
| 0.1079 | 2.0 | 3898 | 0.0851 | 0.9680 | 0.9801 | 0.9740 | 0.9795 |
| 0.0904 | 3.0 | 5847 | 0.0717 | 0.9733 | 0.9842 | 0.9787 | 0.9823 |
| 0.0788 | 4.0 | 7796 | 0.0612 | 0.9773 | 0.9859 | 0.9816 | 0.9845 |
| 0.0709 | 5.0 | 9745 | 0.0548 | 0.9824 | 0.9843 | 0.9833 | 0.9858 |
| 0.0646 | 6.0 | 11694 | 0.0483 | 0.9847 | 0.9890 | 0.9868 | 0.9876 |
| 0.0579 | 7.0 | 13643 | 0.0426 | 0.9875 | 0.9889 | 0.9882 | 0.9889 |
| 0.0532 | 8.0 | 15592 | 0.0385 | 0.9897 | 0.9889 | 0.9893 | 0.9898 |
| 0.0477 | 9.0 | 17541 | 0.0320 | 0.9913 | 0.9932 | 0.9922 | 0.9916 |
| 0.044 | 10.0 | 19490 | 0.0268 | 0.9926 | 0.9952 | 0.9939 | 0.9929 |
| 0.0401 | 11.0 | 21439 | 0.0232 | 0.9937 | 0.9960 | 0.9949 | 0.9936 |
| 0.0366 | 12.0 | 23388 | 0.0200 | 0.9957 | 0.9961 | 0.9959 | 0.9944 |
| 0.0317 | 13.0 | 25337 | 0.0172 | 0.9968 | 0.9969 | 0.9968 | 0.9953 |
| 0.0294 | 14.0 | 27286 | 0.0146 | 0.9971 | 0.9979 | 0.9975 | 0.9959 |
| 0.0269 | 15.0 | 29235 | 0.0126 | 0.9979 | 0.9982 | 0.9981 | 0.9965 |
| 0.0248 | 16.0 | 31184 | 0.0119 | 0.9984 | 0.9982 | 0.9983 | 0.9968 |
| 0.0228 | 17.0 | 33133 | 0.0098 | 0.9987 | 0.9987 | 0.9987 | 0.9973 |
| 0.0203 | 18.0 | 35082 | 0.0091 | 0.9989 | 0.9987 | 0.9988 | 0.9975 |
| 0.0189 | 19.0 | 37031 | 0.0087 | 0.9990 | 0.9989 | 0.9990 | 0.9976 |
| 0.0198 | 20.0 | 38980 | 0.0086 | 0.9991 | 0.9990 | 0.9990 | 0.9977 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3
|