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---
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
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