|
--- |
|
license: apache-2.0 |
|
base_model: distilbert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imdb |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: N_distilbert_imdb_padding30model |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: imdb |
|
type: imdb |
|
config: plain_text |
|
split: test |
|
args: plain_text |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.93196 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# N_distilbert_imdb_padding30model |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7513 |
|
- Accuracy: 0.9320 |
|
|
|
## 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: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.2412 | 1.0 | 1563 | 0.2749 | 0.9004 | |
|
| 0.1694 | 2.0 | 3126 | 0.2355 | 0.9270 | |
|
| 0.1055 | 3.0 | 4689 | 0.3029 | 0.9262 | |
|
| 0.0621 | 4.0 | 6252 | 0.3240 | 0.9282 | |
|
| 0.0422 | 5.0 | 7815 | 0.4462 | 0.9269 | |
|
| 0.0366 | 6.0 | 9378 | 0.4963 | 0.9274 | |
|
| 0.0309 | 7.0 | 10941 | 0.5017 | 0.9286 | |
|
| 0.0189 | 8.0 | 12504 | 0.6588 | 0.9198 | |
|
| 0.0217 | 9.0 | 14067 | 0.5946 | 0.9218 | |
|
| 0.02 | 10.0 | 15630 | 0.6104 | 0.9248 | |
|
| 0.0112 | 11.0 | 17193 | 0.5921 | 0.9293 | |
|
| 0.0096 | 12.0 | 18756 | 0.6499 | 0.9290 | |
|
| 0.0075 | 13.0 | 20319 | 0.6577 | 0.9299 | |
|
| 0.0036 | 14.0 | 21882 | 0.6225 | 0.9289 | |
|
| 0.0043 | 15.0 | 23445 | 0.6558 | 0.9290 | |
|
| 0.0015 | 16.0 | 25008 | 0.6923 | 0.9314 | |
|
| 0.0036 | 17.0 | 26571 | 0.7606 | 0.9284 | |
|
| 0.0 | 18.0 | 28134 | 0.7696 | 0.931 | |
|
| 0.0028 | 19.0 | 29697 | 0.7493 | 0.9319 | |
|
| 0.0005 | 20.0 | 31260 | 0.7513 | 0.9320 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
