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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: distilbert_imdb_padding70model
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: 0.93036
---
<!-- 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_imdb_padding70model
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: 0.7503
- Accuracy: 0.9304
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2385 | 1.0 | 1563 | 0.2404 | 0.9121 |
| 0.1808 | 2.0 | 3126 | 0.2250 | 0.9273 |
| 0.1148 | 3.0 | 4689 | 0.3192 | 0.9253 |
| 0.0711 | 4.0 | 6252 | 0.3479 | 0.9272 |
| 0.0566 | 5.0 | 7815 | 0.4082 | 0.9260 |
| 0.0409 | 6.0 | 9378 | 0.4675 | 0.9268 |
| 0.028 | 7.0 | 10941 | 0.4345 | 0.9268 |
| 0.0209 | 8.0 | 12504 | 0.5870 | 0.9224 |
| 0.0228 | 9.0 | 14067 | 0.4920 | 0.9269 |
| 0.0132 | 10.0 | 15630 | 0.5973 | 0.9248 |
| 0.013 | 11.0 | 17193 | 0.5962 | 0.9282 |
| 0.0127 | 12.0 | 18756 | 0.6695 | 0.9245 |
| 0.0028 | 13.0 | 20319 | 0.7241 | 0.9269 |
| 0.0102 | 14.0 | 21882 | 0.5935 | 0.9298 |
| 0.0033 | 15.0 | 23445 | 0.6654 | 0.9287 |
| 0.0039 | 16.0 | 25008 | 0.6902 | 0.9299 |
| 0.0012 | 17.0 | 26571 | 0.7281 | 0.9281 |
| 0.0023 | 18.0 | 28134 | 0.7369 | 0.9306 |
| 0.0001 | 19.0 | 29697 | 0.7462 | 0.9307 |
| 0.0019 | 20.0 | 31260 | 0.7503 | 0.9304 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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