LED-Large-NSPCC
This model is a fine-tuned version of allenai/led-large-16384 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7268
- Rouge1: 0.5254
- Rouge2: 0.2338
- Rougel: 0.3002
- Rougelsum: 0.3002
- Gen Len: 299.4787
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
2.4641 | 0.9947 | 94 | 2.1400 | 0.4307 | 0.1505 | 0.226 | 0.226 | 353.6277 |
1.8933 | 2.0 | 189 | 1.8349 | 0.4851 | 0.1895 | 0.2638 | 0.2641 | 275.5745 |
1.3745 | 2.9947 | 283 | 1.6659 | 0.516 | 0.2274 | 0.2882 | 0.2887 | 299.5426 |
0.8719 | 3.9788 | 376 | 1.7268 | 0.5254 | 0.2338 | 0.3002 | 0.3002 | 299.4787 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Downloads last month
- 91
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for scott156/LED-Large-NSPCC
Base model
allenai/led-large-16384