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---
tags:
- generated_from_trainer
datasets:
- xsum
model-index:
- name: retnet-Final-smallest-summarization
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. -->
# retnet-Final-smallest-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: 5.1417
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.8127 | 1.0 | 5762 | 5.3184 |
| 5.2364 | 2.0 | 11525 | 5.1682 |
| 5.1518 | 3.0 | 17286 | 5.1417 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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