metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- eur-lex-sum
metrics:
- rouge
model-index:
- name: summary_cz_eurlex
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: eur-lex-sum
type: eur-lex-sum
config: czech
split: test
args: czech
metrics:
- name: Rouge1
type: rouge
value: 0.0181
summary_cz_eurlex
This model is a fine-tuned version of t5-small on the eur-lex-sum dataset. It achieves the following results on the evaluation set:
- Loss: 2.8559
- Rouge1: 0.0181
- Rouge2: 0.0155
- Rougel: 0.0181
- Rougelsum: 0.0181
- Gen Len: 19.0
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 8 | 6.7050 | 0.0181 | 0.0155 | 0.0181 | 0.0181 | 19.0 |
| No log | 2.0 | 16 | 3.3004 | 0.0181 | 0.0155 | 0.0181 | 0.0181 | 19.0 |
| No log | 3.0 | 24 | 2.9529 | 0.0181 | 0.0155 | 0.0181 | 0.0181 | 19.0 |
| No log | 4.0 | 32 | 2.8559 | 0.0181 | 0.0155 | 0.0181 | 0.0181 | 19.0 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1