File size: 1,753 Bytes
75a4ea3 |
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 |
---
license: gpl-3.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: albert-base-chinese-finetuned-qqp
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. -->
# albert-base-chinese-finetuned-qqp
This model is a fine-tuned version of [ckiplab/albert-base-chinese](https://huggingface.co/ckiplab/albert-base-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3385688364505768
- Accuracy: 0.8357142857142857
- F1: 0.8244274809160306
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log | 1.0 | 30 | 0.654749 | 0.642857 | 0.719101 |
| No log | 2.0 | 60 | 0.614816 | 0.728571 | 0.707692 |
| No log | 3.0 | 90 | 0.443354 | 0.807143 | 0.802920 |
| No log | 4.0 | 120 | 0.338569 | 0.835714 | 0.824427 |
| No log | 5.0 | 150 | 0.339324 | 0.828571 | 0.806452 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.0.dev0
|