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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-imdb
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: imdb
type: imdb
args: plain_text
metrics:
- type: accuracy
value: 0.9214
name: Accuracy
---
<!-- 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-base-uncased-imdb
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an imdb dataset where an evaluation of 5000 samples was created by splitting the training set.
It achieves the following results on the evaluation set:
- Loss: 0.6252
- Accuracy: 0.9214
## Model description
More information needed
## Intended uses & limitations
This model was trained for the introduction to Natural language processing course of [EPITA](https://www.epita.fr/).
## Training and evaluation data
The training/evaluation split was generated using a `seed` of 42 and a `test_size` of 0.2.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 128
- seed: 1337
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2875 | 1.0 | 625 | 0.2286 | 0.9102 |
| 0.1685 | 2.0 | 1250 | 0.2416 | 0.9128 |
| 0.1171 | 3.0 | 1875 | 0.3223 | 0.917 |
| 0.0493 | 4.0 | 2500 | 0.3667 | 0.9162 |
| 0.023 | 5.0 | 3125 | 0.4074 | 0.92 |
| 0.015 | 6.0 | 3750 | 0.4291 | 0.9236 |
| 0.0129 | 7.0 | 4375 | 0.5452 | 0.9194 |
| 0.0051 | 8.0 | 5000 | 0.5886 | 0.9146 |
| 0.0027 | 9.0 | 5625 | 0.6310 | 0.9186 |
| 0.002 | 10.0 | 6250 | 0.6252 | 0.9214 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|