metadata
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: ML5-fine-tuning-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.5714
ML5-fine-tuning-xsum
This model is a fine-tuned version of google/mt5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 7.4333
- Rouge1: 0.5714
- Rouge2: 0.0
- Rougel: 0.5714
- Rougelsum: 0.5714
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 18.7065 | 1.0 | 7 | 9.6966 | 0.0 | 0.0 | 0.0 | 0.0 |
| 10.3198 | 2.0 | 14 | 7.4333 | 0.5714 | 0.0 | 0.5714 | 0.5714 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.3.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1