---
library_name: transformers
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: longformer-combined-2epoch
  results: []
---

<!-- 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. -->

# longformer-combined-2epoch

This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4259
- Accuracy: 0.71
- F1: 0.6410

## 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: 5e-05
- train_batch_size: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.7476        | 0.0556 | 50   | 0.7044          | 0.494    | 0.3308 |
| 0.7543        | 0.1111 | 100  | 0.7187          | 0.5215   | 0.3427 |
| 0.6395        | 0.1667 | 150  | 0.7392          | 0.5215   | 0.3427 |
| 0.6322        | 0.2222 | 200  | 0.5797          | 0.648    | 0.5771 |
| 0.5879        | 0.2778 | 250  | 0.5351          | 0.678    | 0.5905 |
| 0.5179        | 0.3333 | 300  | 0.5117          | 0.6975   | 0.6116 |
| 0.5868        | 0.3889 | 350  | 0.5010          | 0.704    | 0.6184 |
| 0.4915        | 0.4444 | 400  | 0.4662          | 0.72     | 0.6348 |
| 0.5408        | 0.5    | 450  | 0.5064          | 0.67     | 0.5990 |
| 0.4393        | 0.5556 | 500  | 0.4584          | 0.6965   | 0.6271 |
| 0.4974        | 0.6111 | 550  | 0.4894          | 0.688    | 0.6183 |
| 0.461         | 0.6667 | 600  | 0.4711          | 0.688    | 0.6184 |
| 0.4446        | 0.7222 | 650  | 0.4520          | 0.719    | 0.6338 |
| 0.4059        | 0.7778 | 700  | 0.5283          | 0.703    | 0.6166 |
| 0.4914        | 0.8333 | 750  | 0.4977          | 0.6655   | 0.5949 |
| 0.4506        | 0.8889 | 800  | 0.4973          | 0.7155   | 0.6303 |
| 0.4433        | 0.9444 | 850  | 0.4571          | 0.6935   | 0.6239 |
| 0.5217        | 1.0    | 900  | 0.4675          | 0.6875   | 0.6177 |
| 0.5323        | 1.0556 | 950  | 0.4639          | 0.691    | 0.6213 |
| 0.4469        | 1.1111 | 1000 | 0.4869          | 0.6815   | 0.6116 |
| 0.4435        | 1.1667 | 1050 | 0.4606          | 0.698    | 0.6286 |
| 0.4596        | 1.2222 | 1100 | 0.4464          | 0.7235   | 0.6384 |
| 0.4454        | 1.2778 | 1150 | 0.4574          | 0.6985   | 0.6291 |
| 0.4308        | 1.3333 | 1200 | 0.4343          | 0.7295   | 0.6446 |
| 0.4656        | 1.3889 | 1250 | 0.4517          | 0.7235   | 0.6384 |
| 0.4057        | 1.4444 | 1300 | 0.4412          | 0.7035   | 0.6343 |
| 0.4322        | 1.5    | 1350 | 0.4306          | 0.7035   | 0.6343 |
| 0.417         | 1.5556 | 1400 | 0.4269          | 0.7305   | 0.6457 |
| 0.3974        | 1.6111 | 1450 | 0.4333          | 0.7295   | 0.6447 |
| 0.41          | 1.6667 | 1500 | 0.4340          | 0.7045   | 0.6354 |
| 0.4132        | 1.7222 | 1550 | 0.4532          | 0.7005   | 0.6312 |
| 0.445         | 1.7778 | 1600 | 0.4399          | 0.733    | 0.6482 |
| 0.4159        | 1.8333 | 1650 | 0.4374          | 0.7325   | 0.6477 |
| 0.3858        | 1.8889 | 1700 | 0.4234          | 0.735    | 0.6503 |
| 0.4641        | 1.9444 | 1750 | 0.4244          | 0.737    | 0.6524 |
| 0.3893        | 2.0    | 1800 | 0.4259          | 0.71     | 0.6410 |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1