
<!-- 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. -->

# Bart_reddit_tifu

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the reddit_tifu dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5035
- Rouge1: 0.2709
- Rouge2: 0.0948
- Rougel: 0.2244
- Rougelsum: 0.2244
- Gen Len: 19.3555
- Precision: 0.8768
- Recall: 0.8648
- F1: 0.8705

## 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: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
| 2.6968        | 1.0   | 2370 | 2.5385          | 0.2634 | 0.0907 | 0.218  | 0.2182    | 19.4438 | 0.8766    | 0.8641 | 0.8701 |
| 2.4746        | 2.0   | 4741 | 2.5077          | 0.273  | 0.0941 | 0.2238 | 0.2239    | 19.2572 | 0.8774    | 0.8655 | 0.8712 |
| 2.3066        | 3.0   | 7111 | 2.5012          | 0.2671 | 0.0936 | 0.221  | 0.2211    | 19.3071 | 0.8756    | 0.864  | 0.8696 |
| 2.2041        | 4.0   | 9480 | 2.5035          | 0.2709 | 0.0948 | 0.2244 | 0.2244    | 19.3555 | 0.8768    | 0.8648 | 0.8705 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["reddit_tifu"], "metrics": ["rouge", "precision", "recall", "f1"], "base_model": "facebook/bart-large", "model-index": [{"name": "Bart_reddit_tifu", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "reddit_tifu", "type": "reddit_tifu", "config": "long", "split": "train", "args": "long"}, "metrics": [{"type": "rouge", "value": 0.2709, "name": "Rouge1"}, {"type": "precision", "value": 0.8768, "name": "Precision"}, {"type": "recall", "value": 0.8648, "name": "Recall"}, {"type": "f1", "value": 0.8705, "name": "F1"}]}]}]}
transformers tensorboard safetensors bart text2text-generation generated_from_trainer dataset:reddit_tifu base_model:facebook/bart-large license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us