|
--- |
|
license: apache-2.0 |
|
base_model: distilbert/distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert_distilbert-base-uncased-15-epoch |
|
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_distilbert-base-uncased-15-epoch |
|
|
|
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: 6.5739 |
|
- Accuracy: 0.4129 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- 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 | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 1.2998 | 1.0 | 5714 | 1.3409 | 0.3419 | |
|
| 1.1366 | 2.0 | 11428 | 1.3753 | 0.3634 | |
|
| 0.9035 | 3.0 | 17142 | 1.4999 | 0.3794 | |
|
| 0.6883 | 4.0 | 22856 | 1.7468 | 0.3906 | |
|
| 0.5177 | 5.0 | 28570 | 2.1011 | 0.3997 | |
|
| 0.3968 | 6.0 | 34284 | 2.2910 | 0.4009 | |
|
| 0.2936 | 7.0 | 39998 | 2.8000 | 0.4121 | |
|
| 0.2403 | 8.0 | 45712 | 2.7002 | 0.4086 | |
|
| 0.1843 | 9.0 | 51426 | 3.4014 | 0.4160 | |
|
| 0.1478 | 10.0 | 57140 | 3.5690 | 0.4057 | |
|
| 0.1231 | 11.0 | 62854 | 4.3858 | 0.4102 | |
|
| 0.1027 | 12.0 | 68568 | 4.6814 | 0.4124 | |
|
| 0.0897 | 13.0 | 74282 | 4.9962 | 0.4186 | |
|
| 0.0823 | 14.0 | 79996 | 6.0199 | 0.4160 | |
|
| 0.0631 | 15.0 | 85710 | 6.5739 | 0.4129 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.0.dev0 |
|
- Pytorch 2.2.0+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.0 |
|
|