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: 1.6129
- Rouge1: 0.5117
- Rouge2: 0.2276
- Rougel: 0.2877
- Rougelsum: 0.2864
- Gen Len: 317.0532
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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.2026 | 0.99 | 94 | 1.8032 | 0.3532 | 0.1387 | 0.1944 | 0.1935 | 189.117 |
| 1.3273 | 1.99 | 188 | 1.6129 | 0.5117 | 0.2276 | 0.2877 | 0.2864 | 317.0532 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for scott156/LEDLargeNSPCCV1
Base model
allenai/led-large-16384