metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- fairytale_qa
metrics:
- rouge
- f1
model-index:
- name: t5-small-finetuned-FairytaleQA-AnswerExtraction
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: fairytale_qa
type: fairytale_qa
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 10.7124
- name: F1
type: f1
value: 0.2626
t5-small-finetuned-FairytaleQA-AnswerExtraction
This model is a fine-tuned version of t5-small on the fairytale_qa dataset. It achieves the following results on the evaluation set:
- Loss: 0.0695
- Rouge1: 10.7124
- Rouge2: 3.2292
- Rougel: 10.375
- Rougelsum: 10.3824
- F1: 0.2626
- Exact Match: 0.4878
- Gen Len: 11.9668
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | F1 | Exact Match | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.0777 | 1.0 | 2137 | 0.0727 | 11.076 | 3.0967 | 10.6128 | 10.6396 | 0.1301 | 0.3902 | 12.522 |
| 0.0727 | 2.0 | 4274 | 0.0707 | 11.288 | 3.2828 | 10.9125 | 10.9225 | 0.152 | 0.4878 | 12.161 |
| 0.0696 | 3.0 | 6411 | 0.0699 | 10.7512 | 3.3182 | 10.406 | 10.4123 | 0.2626 | 0.4878 | 12.1122 |
| 0.0719 | 4.0 | 8548 | 0.0696 | 10.803 | 3.2133 | 10.4337 | 10.4223 | 0.2626 | 0.4878 | 11.9698 |
| 0.07 | 5.0 | 10685 | 0.0695 | 10.7124 | 3.2292 | 10.375 | 10.3824 | 0.2626 | 0.4878 | 11.9668 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1