---
license: apache-2.0
base_model: allenai/longformer-base-4096
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: 0.95528
---

<!-- 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 [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2141
- Accuracy: 0.9553

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3358        | 0.32  | 1000 | 0.2286          | 0.9349   |
| 0.2658        | 0.64  | 2000 | 0.2036          | 0.9447   |
| 0.2392        | 0.96  | 3000 | 0.2294          | 0.9504   |
| 0.1648        | 1.28  | 4000 | 0.2288          | 0.9518   |
| 0.1477        | 1.6   | 5000 | 0.2190          | 0.9532   |
| 0.1404        | 1.92  | 6000 | 0.2141          | 0.9553   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1