metadata
license: apache-2.0
base_model: gsarti/it5-small
tags:
- generated_from_trainer
datasets:
- geopolitica
metrics:
- rouge
model-index:
- name: my_awesome_geopolitical_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: geopolitica
type: geopolitica
config: default
split: train
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.1409
my_awesome_geopolitical_model
This model is a fine-tuned version of gsarti/it5-small on the geopolitica dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.1409
- Rouge2: 0.0203
- Rougel: 0.1247
- Rougelsum: 0.125
- Gen Len: 18.781
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 53 | nan | 0.1409 | 0.0203 | 0.1247 | 0.125 | 18.781 |
| No log | 2.0 | 106 | nan | 0.1409 | 0.0203 | 0.1247 | 0.125 | 18.781 |
| No log | 3.0 | 159 | nan | 0.1409 | 0.0203 | 0.1247 | 0.125 | 18.781 |
| No log | 4.0 | 212 | nan | 0.1409 | 0.0203 | 0.1247 | 0.125 | 18.781 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3