|
--- |
|
license: apache-2.0 |
|
base_model: bert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imdb |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: N_bert_imdb_padding40model |
|
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: 0.939 |
|
--- |
|
|
|
<!-- 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_bert_imdb_padding40model |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6742 |
|
- Accuracy: 0.939 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.2234 | 1.0 | 1563 | 0.2483 | 0.9251 | |
|
| 0.1543 | 2.0 | 3126 | 0.2148 | 0.9323 | |
|
| 0.0957 | 3.0 | 4689 | 0.2969 | 0.9329 | |
|
| 0.0674 | 4.0 | 6252 | 0.3085 | 0.9369 | |
|
| 0.035 | 5.0 | 7815 | 0.3765 | 0.9367 | |
|
| 0.0398 | 6.0 | 9378 | 0.4149 | 0.9368 | |
|
| 0.0215 | 7.0 | 10941 | 0.4424 | 0.9376 | |
|
| 0.0162 | 8.0 | 12504 | 0.4885 | 0.9352 | |
|
| 0.0113 | 9.0 | 14067 | 0.4668 | 0.935 | |
|
| 0.0168 | 10.0 | 15630 | 0.5267 | 0.9367 | |
|
| 0.0077 | 11.0 | 17193 | 0.5049 | 0.9378 | |
|
| 0.0082 | 12.0 | 18756 | 0.5595 | 0.9374 | |
|
| 0.0055 | 13.0 | 20319 | 0.5650 | 0.9341 | |
|
| 0.0035 | 14.0 | 21882 | 0.6518 | 0.9356 | |
|
| 0.0017 | 15.0 | 23445 | 0.6662 | 0.9385 | |
|
| 0.0036 | 16.0 | 25008 | 0.6536 | 0.9369 | |
|
| 0.0 | 17.0 | 26571 | 0.7483 | 0.9354 | |
|
| 0.0003 | 18.0 | 28134 | 0.7027 | 0.9368 | |
|
| 0.0034 | 19.0 | 29697 | 0.6818 | 0.9384 | |
|
| 0.0008 | 20.0 | 31260 | 0.6742 | 0.939 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|