| --- |
| license: apache-2.0 |
| base_model: allenai/led-base-16384 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: LED-Base-NSPCC |
| 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. --> |
|
|
| # LED-Base-NSPCC |
|
|
| This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.8152 |
| - Rouge1: 0.4955 |
| - Rouge2: 0.2131 |
| - Rougel: 0.2804 |
| - Rougelsum: 0.2807 |
| - Gen Len: 267.3511 |
|
|
| ## 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: 0.0003 |
| - 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: cosine |
| - lr_scheduler_warmup_ratio: 0.03 |
| - num_epochs: 2 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:| |
| | 2.5412 | 0.99 | 47 | 1.9338 | 0.4778 | 0.186 | 0.2638 | 0.2635 | 266.2766 | |
| | 1.6145 | 1.99 | 94 | 1.8152 | 0.4955 | 0.2131 | 0.2804 | 0.2807 | 267.3511 | |
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| ### Framework versions |
|
|
| - Transformers 4.39.3 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
