|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert-mouse-enhancers |
|
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. --> |
|
|
|
# distilbert-mouse-enhancers |
|
|
|
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6932 |
|
- Accuracy: 0.5 |
|
|
|
## 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-06 |
|
- 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: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| No log | 1.0 | 242 | 0.6932 | 0.5 | |
|
| No log | 2.0 | 484 | 0.6949 | 0.5 | |
|
| 0.693 | 3.0 | 726 | 0.6931 | 0.5 | |
|
| 0.693 | 4.0 | 968 | 0.6931 | 0.5 | |
|
| 0.694 | 5.0 | 1210 | 0.6932 | 0.5 | |
|
| 0.694 | 6.0 | 1452 | 0.6935 | 0.5 | |
|
| 0.6954 | 7.0 | 1694 | 0.6933 | 0.5 | |
|
| 0.6954 | 8.0 | 1936 | 0.6932 | 0.5 | |
|
| 0.6937 | 9.0 | 2178 | 0.6932 | 0.5 | |
|
| 0.6937 | 10.0 | 2420 | 0.6932 | 0.5 | |
|
| 0.6935 | 11.0 | 2662 | 0.6932 | 0.5 | |
|
| 0.6935 | 12.0 | 2904 | 0.6934 | 0.5 | |
|
| 0.6955 | 13.0 | 3146 | 0.6932 | 0.5 | |
|
| 0.6955 | 14.0 | 3388 | 0.6931 | 0.5 | |
|
| 0.6941 | 15.0 | 3630 | 0.6931 | 0.5 | |
|
| 0.6941 | 16.0 | 3872 | 0.6932 | 0.5 | |
|
| 0.6953 | 17.0 | 4114 | 0.6932 | 0.5 | |
|
| 0.6953 | 18.0 | 4356 | 0.6931 | 0.5 | |
|
| 0.6932 | 19.0 | 4598 | 0.6932 | 0.5 | |
|
| 0.6932 | 20.0 | 4840 | 0.6931 | 0.5 | |
|
| 0.6945 | 21.0 | 5082 | 0.6933 | 0.5 | |
|
| 0.6945 | 22.0 | 5324 | 0.6932 | 0.5 | |
|
| 0.6939 | 23.0 | 5566 | 0.6931 | 0.5 | |
|
| 0.6939 | 24.0 | 5808 | 0.6931 | 0.5 | |
|
| 0.6951 | 25.0 | 6050 | 0.6932 | 0.5 | |
|
| 0.6951 | 26.0 | 6292 | 0.6931 | 0.5 | |
|
| 0.6943 | 27.0 | 6534 | 0.6932 | 0.5 | |
|
| 0.6943 | 28.0 | 6776 | 0.6931 | 0.5 | |
|
| 0.6944 | 29.0 | 7018 | 0.6931 | 0.5 | |
|
| 0.6944 | 30.0 | 7260 | 0.6932 | 0.5 | |
|
| 0.6955 | 31.0 | 7502 | 0.6931 | 0.5 | |
|
| 0.6955 | 32.0 | 7744 | 0.6933 | 0.5 | |
|
| 0.6955 | 33.0 | 7986 | 0.6932 | 0.5 | |
|
| 0.694 | 34.0 | 8228 | 0.6931 | 0.5 | |
|
| 0.694 | 35.0 | 8470 | 0.6932 | 0.5 | |
|
| 0.6937 | 36.0 | 8712 | 0.6932 | 0.5 | |
|
| 0.6937 | 37.0 | 8954 | 0.6931 | 0.5 | |
|
| 0.6923 | 38.0 | 9196 | 0.6932 | 0.5 | |
|
| 0.6923 | 39.0 | 9438 | 0.6932 | 0.5 | |
|
| 0.6931 | 40.0 | 9680 | 0.6931 | 0.5 | |
|
| 0.6931 | 41.0 | 9922 | 0.6932 | 0.5 | |
|
| 0.6937 | 42.0 | 10164 | 0.6932 | 0.5 | |
|
| 0.6937 | 43.0 | 10406 | 0.6932 | 0.5 | |
|
| 0.6936 | 44.0 | 10648 | 0.6932 | 0.5 | |
|
| 0.6936 | 45.0 | 10890 | 0.6932 | 0.5 | |
|
| 0.6933 | 46.0 | 11132 | 0.6932 | 0.5 | |
|
| 0.6933 | 47.0 | 11374 | 0.6932 | 0.5 | |
|
| 0.6924 | 48.0 | 11616 | 0.6932 | 0.5 | |
|
| 0.6924 | 49.0 | 11858 | 0.6932 | 0.5 | |
|
| 0.6929 | 50.0 | 12100 | 0.6932 | 0.5 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 2.0.0+cu117 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.13.3 |
|
|
