metadata
base_model: >-
/exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360
tags:
- generated_from_trainer
datasets:
- learn3r/gov_report_memsum_bp
metrics:
- rouge
model-index:
- name: longt5_xl_gov_memsum_bp_20
results:
- task:
name: Summarization
type: summarization
dataset:
name: learn3r/gov_report_memsum_bp
type: learn3r/gov_report_memsum_bp
metrics:
- name: Rouge1
type: rouge
value: 42.5601
longt5_xl_gov_memsum_bp_20
This model is a fine-tuned version of /exports/eddie/scratch/s1970716/models/summarization/longt5_xl_gov_memsum_bp_15/checkpoint-1360 on the learn3r/gov_report_memsum_bp dataset. It achieves the following results on the evaluation set:
- Loss: 3.6259
- Rouge1: 42.5601
- Rouge2: 14.1791
- Rougel: 17.9691
- Rougelsum: 40.487
- Gen Len: 1510.8695
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: 0.001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.1591 | 1.0 | 136 | 3.6259 | 42.5601 | 14.1791 | 17.9691 | 40.487 | 1510.8695 |
| 0.1186 | 1.99 | 272 | 3.7885 | 39.795 | 13.2493 | 17.3095 | 37.9065 | 1707.0401 |
| 0.097 | 3.0 | 409 | 4.0192 | 41.4441 | 13.4026 | 17.8804 | 39.4502 | 1442.7729 |
| 0.0818 | 4.0 | 545 | 4.1699 | 40.2374 | 13.5869 | 17.364 | 38.2969 | 1741.0236 |
| 0.0786 | 4.99 | 680 | 4.3339 | 39.5612 | 13.4283 | 17.3666 | 37.6526 | 1710.4111 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1