transformers tensorboard safetensors distilbert text-classification generated_from_trainer dataset:imdb base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert/distilbert-base-uncased
datasets:
- imdb
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: my_awesome_model
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: imdb
      type: imdb
      config: plain_text
      split: test
      args: plain_text
    metrics:
    - type: accuracy
      value: 0.85588
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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
