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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: N_distilbert_imdb_padding100model
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: 0.92944
---
<!-- 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_padding100model
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: 0.7393
- Accuracy: 0.9294
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2387 | 1.0 | 1563 | 0.2354 | 0.919 |
| 0.1866 | 2.0 | 3126 | 0.2345 | 0.9248 |
| 0.1194 | 3.0 | 4689 | 0.3117 | 0.9212 |
| 0.0615 | 4.0 | 6252 | 0.3370 | 0.9219 |
| 0.0475 | 5.0 | 7815 | 0.5367 | 0.9131 |
| 0.0394 | 6.0 | 9378 | 0.5018 | 0.9236 |
| 0.0281 | 7.0 | 10941 | 0.5039 | 0.9243 |
| 0.0262 | 8.0 | 12504 | 0.5149 | 0.9238 |
| 0.0203 | 9.0 | 14067 | 0.5159 | 0.9275 |
| 0.0194 | 10.0 | 15630 | 0.5855 | 0.927 |
| 0.0092 | 11.0 | 17193 | 0.6452 | 0.9259 |
| 0.0097 | 12.0 | 18756 | 0.6318 | 0.9262 |
| 0.0024 | 13.0 | 20319 | 0.6537 | 0.9292 |
| 0.0056 | 14.0 | 21882 | 0.7551 | 0.9268 |
| 0.0037 | 15.0 | 23445 | 0.7516 | 0.9255 |
| 0.0073 | 16.0 | 25008 | 0.7335 | 0.9281 |
| 0.0025 | 17.0 | 26571 | 0.6959 | 0.9301 |
| 0.0008 | 18.0 | 28134 | 0.7439 | 0.9276 |
| 0.0005 | 19.0 | 29697 | 0.7300 | 0.9296 |
| 0.0004 | 20.0 | 31260 | 0.7393 | 0.9294 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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