Edit model card

LongT5-Large-NSPCC

This model is a fine-tuned version of google/long-t5-tglobal-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5481
  • Rouge1: 0.4597
  • Rouge2: 0.1665
  • Rougel: 0.2562
  • Rougelsum: 0.2557
  • Gen Len: 250.6383

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 6

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
6.0521 1.0 188 2.8154 0.2268 0.0411 0.1627 0.1626 145.7447
2.5796 2.0 377 1.9961 0.3798 0.1115 0.2103 0.2101 220.234
2.0398 3.0 566 1.7703 0.4208 0.1319 0.2255 0.2258 299.6915
1.7329 4.0 755 1.5996 0.4427 0.1488 0.2423 0.2424 255.2553
1.5609 5.0 943 1.5510 0.4688 0.1726 0.2578 0.2576 289.2979
1.4733 5.98 1128 1.5481 0.4597 0.1665 0.2562 0.2557 250.6383

Framework versions

  • Transformers 4.39.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
1
Safetensors
Model size
783M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for scott156/LongT5-Large-NSPCC

Finetuned
(3)
this model