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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: my_awesome_model
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: 0.85588
---
<!-- 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. -->
# my_awesome_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8771
- Accuracy: 0.8559
## 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: 1e-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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3564 | 1.0 | 1563 | 0.3677 | 0.8426 |
| 0.2878 | 2.0 | 3126 | 0.3378 | 0.8588 |
| 0.2124 | 3.0 | 4689 | 0.4398 | 0.8550 |
| 0.1556 | 4.0 | 6252 | 0.5750 | 0.8555 |
| 0.1075 | 5.0 | 7815 | 0.6733 | 0.8558 |
| 0.0831 | 6.0 | 9378 | 0.7218 | 0.8561 |
| 0.0652 | 7.0 | 10941 | 0.7331 | 0.8564 |
| 0.0458 | 8.0 | 12504 | 0.8166 | 0.8538 |
| 0.0415 | 9.0 | 14067 | 0.8619 | 0.8568 |
| 0.0357 | 10.0 | 15630 | 0.8771 | 0.8559 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
|