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# retnet-Final-summarization

This model is a fine-tuned version of [](https://huggingface.co/) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2285

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 4.9417        | 1.0   | 5762  | 4.4472          |
| 4.3331        | 2.0   | 11525 | 4.2671          |
| 4.2108        | 3.0   | 17286 | 4.2285          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "datasets": ["xsum"], "model-index": [{"name": "retnet-Final-summarization", "results": []}]}
transformers tensorboard safetensors retnet text-generation generated_from_trainer dataset:xsum autotrain_compatible endpoints_compatible region:us