metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.0706
mt5-small-finetuned-amazon-en-es
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: 5.4800
- Rouge1: 0.0706
- Rouge2: 0.0067
- Rougel: 0.058
- Rougelsum: 0.0654
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: 5.6e-05
- 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 13 | 7.7221 | 0.0369 | 0.0 | 0.0369 | 0.0366 |
| No log | 2.0 | 26 | 7.1952 | 0.0448 | 0.0 | 0.0452 | 0.0449 |
| No log | 3.0 | 39 | 6.5146 | 0.0442 | 0.0 | 0.0443 | 0.044 |
| 12.6754 | 4.0 | 52 | 6.2530 | 0.0745 | 0.008 | 0.0636 | 0.0679 |
| 12.6754 | 5.0 | 65 | 6.0200 | 0.0745 | 0.0069 | 0.0642 | 0.0693 |
| 12.6754 | 6.0 | 78 | 5.7336 | 0.0706 | 0.0067 | 0.058 | 0.0654 |
| 12.6754 | 7.0 | 91 | 5.5400 | 0.0706 | 0.0067 | 0.058 | 0.0654 |
| 9.1744 | 8.0 | 104 | 5.4800 | 0.0706 | 0.0067 | 0.058 | 0.0654 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2