File size: 2,059 Bytes
75621bc |
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 |
---
license: apache-2.0
base_model: Langboat/mengzi-bert-base-fin
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSE50-12
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. -->
# mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSE50-12
This model is a fine-tuned version of [Langboat/mengzi-bert-base-fin](https://huggingface.co/Langboat/mengzi-bert-base-fin) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9030
- Accuracy: 0.7879
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 34 | 2.2065 | 0.6667 |
| No log | 2.0 | 68 | 2.7159 | 0.7273 |
| No log | 3.0 | 102 | 2.6006 | 0.6970 |
| No log | 4.0 | 136 | 2.2278 | 0.7273 |
| No log | 5.0 | 170 | 3.0872 | 0.6667 |
| No log | 6.0 | 204 | 1.7348 | 0.7273 |
| No log | 7.0 | 238 | 1.8437 | 0.7879 |
| No log | 8.0 | 272 | 1.7299 | 0.7576 |
| No log | 9.0 | 306 | 1.9420 | 0.7879 |
| No log | 10.0 | 340 | 1.9030 | 0.7879 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|