kobart_16_5.6e-5_datav2_min30_lp5.0_temperature1.0

This model is a fine-tuned version of gogamza/kobart-base-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.7174
• Rouge1: 35.7621
• Rouge2: 12.8914
• Rougel: 23.6695
• Bleu1: 29.9954
• Bleu2: 17.513
• Bleu3: 10.317
• Bleu4: 5.8532
• Gen Len: 49.3147

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: 5.6e-05
• train_batch_size: 16
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Bleu1	Bleu2	Bleu3	Bleu4	Gen Len
1.9617	1.89	5000	2.6146	35.2828	12.4993	22.9894	29.2237	16.8919	9.7826	5.4461	48.0676
1.5272	3.78	10000	2.7174	35.7621	12.8914	23.6695	29.9954	17.513	10.317	5.8532	49.3147

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.1+cu117
• Datasets 2.7.1
• Tokenizers 0.13.2