---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
datasets:
- xlsum-fi
model-index:
- name: allenai/led-base-16384
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# allenai/led-base-16384

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the xlsum-fi dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3962
- Rouge2 Precision: 0.0109
- Rouge2 Recall: 0.0248
- Rouge2 Fmeasure: 0.0152

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 3.8391        | 0.32  | 10   | 3.5714          | 0.0062           | 0.016         | 0.0089          |
| 3.8           | 0.64  | 20   | 3.4777          | 0.0083           | 0.0202        | 0.0115          |
| 3.6502        | 0.96  | 30   | 3.3962          | 0.0109           | 0.0248        | 0.0152          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1