|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: ec_classfication_0502_distilbert_base_uncased |
|
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. --> |
|
|
|
# ec_classfication_0502_distilbert_base_uncased |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9120 |
|
- F1: 0.8222 |
|
|
|
## 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: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| No log | 1.0 | 59 | 0.6145 | 0.5753 | |
|
| No log | 2.0 | 118 | 0.5000 | 0.7619 | |
|
| No log | 3.0 | 177 | 0.5990 | 0.7 | |
|
| No log | 4.0 | 236 | 0.5030 | 0.8235 | |
|
| No log | 5.0 | 295 | 0.6379 | 0.8478 | |
|
| No log | 6.0 | 354 | 0.6739 | 0.8478 | |
|
| No log | 7.0 | 413 | 0.7597 | 0.8090 | |
|
| No log | 8.0 | 472 | 0.7854 | 0.8222 | |
|
| 0.1878 | 9.0 | 531 | 0.8594 | 0.8222 | |
|
| 0.1878 | 10.0 | 590 | 0.8947 | 0.8090 | |
|
| 0.1878 | 11.0 | 649 | 0.9086 | 0.8222 | |
|
| 0.1878 | 12.0 | 708 | 0.9130 | 0.8222 | |
|
| 0.1878 | 13.0 | 767 | 0.9070 | 0.8222 | |
|
| 0.1878 | 14.0 | 826 | 0.9117 | 0.8222 | |
|
| 0.1878 | 15.0 | 885 | 0.9120 | 0.8222 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.3 |
|
- Pytorch 2.0.0+cu118 |
|
- Datasets 2.11.0 |
|
- Tokenizers 0.13.2 |
|
|
