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# longt5_xl_govreport_memsum_4096

This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the learn3r/gov_report_memsum_bp dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9247

## 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: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1429        | 1.0   | 68   | 1.0058          |
| 0.9866        | 1.99  | 136  | 0.9247          |
| 0.9376        | 2.99  | 204  | 0.9298          |
| 0.8714        | 3.99  | 272  | 0.9250          |
| 0.7959        | 5.0   | 341  | 0.9284          |
| 0.729         | 6.0   | 409  | 0.9532          |
| 0.6575        | 6.99  | 477  | 0.9622          |
| 0.6076        | 7.99  | 545  | 0.9937          |
| 0.5653        | 8.99  | 613  | 1.0211          |
| 0.487         | 9.97  | 680  | 1.0659          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["learn3r/gov_report_memsum_bp"], "base_model": "google/long-t5-tglobal-xl", "model-index": [{"name": "longt5_xl_govreport_memsum_4096", "results": []}]}
transformers pytorch longt5 text2text-generation generated_from_trainer dataset:learn3r/gov_report_memsum_bp base_model:google/long-t5-tglobal-xl license:apache-2.0 autotrain_compatible endpoints_compatible region:us