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