metadata
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: continue_pretrain_t5_base_10tokens
results: []
continue_pretrain_t5_base_10tokens
This model is a fine-tuned version of google-t5/t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.0015
- Rouge: {'rouge1': 0.15180664921665177, 'rouge2': 0.14241763000023774, 'rougeL': 0.1513952140128575, 'rougeLsum': 0.1517189553463021}
- Exact Match: {'exact_match': 0.0}
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: 14
- eval_batch_size: 14
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge | Exact Match |
|---|---|---|---|---|---|
| 0.1039 | 1.0 | 1786 | 4.8370 | {'rouge1': 0.08468086761955296, 'rouge2': 0.07928600729695852, 'rougeL': 0.08453698334268148, 'rougeLsum': 0.08473098923719942} | {'exact_match': 0.0} |
| 0.0503 | 2.0 | 3572 | 4.9960 | {'rouge1': 0.15080775818986453, 'rouge2': 0.1414201900527639, 'rougeL': 0.15034957154685738, 'rougeLsum': 0.1506605398259596} | {'exact_match': 0.0} |
| 0.0521 | 3.0 | 5358 | 5.0015 | {'rouge1': 0.15180664921665177, 'rouge2': 0.14241763000023774, 'rougeL': 0.1513952140128575, 'rougeLsum': 0.1517189553463021} | {'exact_match': 0.0} |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1