File size: 2,238 Bytes
4e19ca2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
---
base_model: sanikaska/rut5_gazeta_title_generation
tags:
- generated_from_trainer
datasets:
- gazeta
metrics:
- rouge
model-index:
- name: rut5_gazeta_title_generation
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gazeta
type: gazeta
config: default
split: test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.0594
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# rut5_gazeta_title_generation
This model is a fine-tuned version of [sanikaska/rut5_gazeta_title_generation](https://huggingface.co/sanikaska/rut5_gazeta_title_generation) on the gazeta dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5882
- Rouge1: 0.0594
- Rouge2: 0.0105
- Rougel: 0.0592
- Rougelsum: 0.0592
- Gen Len: 9.6443
## 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: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.756 | 1.0 | 2500 | 2.4833 | 0.0516 | 0.0087 | 0.0514 | 0.0513 | 10.4538 |
| 2.4648 | 2.0 | 5000 | 2.4972 | 0.0583 | 0.0108 | 0.0582 | 0.0581 | 9.9832 |
| 2.306 | 3.0 | 7500 | 2.5375 | 0.0594 | 0.0104 | 0.0592 | 0.0592 | 9.4259 |
| 2.1811 | 4.0 | 10000 | 2.5882 | 0.0594 | 0.0105 | 0.0592 | 0.0592 | 9.6443 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|