metadata
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: SummarEaseV1
results: []
SummarEaseV1
This model is a fine-tuned version of google-t5/t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4382
- Rouge1: 0.2458
- Rouge2: 0.1168
- Rougel: 0.2008
- Rougelsum: 0.2001
- Gen Len: 19.0
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 0.7619 | 3 | 2.5665 | 0.2388 | 0.1118 | 0.1962 | 0.1959 | 19.0 |
| No log | 1.7778 | 7 | 2.4863 | 0.2439 | 0.1153 | 0.2005 | 0.1996 | 19.0 |
| No log | 2.7937 | 11 | 2.4462 | 0.2461 | 0.1169 | 0.2009 | 0.2003 | 19.0 |
| No log | 3.0476 | 12 | 2.4382 | 0.2458 | 0.1168 | 0.2008 | 0.2001 | 19.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1