File size: 2,628 Bytes
4829a0a |
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 84 85 86 87 88 |
---
base_model: kravchenko/uk-mt5-base
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: uk-mt5-base-xlsum-v2
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xlsum
type: xlsum
config: ukrainian
split: validation
args: ukrainian
metrics:
- name: Rouge1
type: rouge
value: 4.4311
---
<!-- 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. -->
# uk-mt5-base-xlsum-v2
This model is a fine-tuned version of [kravchenko/uk-mt5-base](https://huggingface.co/kravchenko/uk-mt5-base) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0401
- Rouge1: 4.4311
- Rouge2: 0.8944
- Rougel: 4.4294
- Rougelsum: 4.4527
## 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.2519 | 1.0 | 2000 | 2.0993 | 4.1141 | 0.5944 | 4.1014 | 4.11 |
| 2.5587 | 2.0 | 4000 | 2.0428 | 4.5015 | 0.6167 | 4.4863 | 4.518 |
| 2.3299 | 3.0 | 6000 | 2.0175 | 4.4642 | 1.0833 | 4.4528 | 4.5167 |
| 2.1543 | 4.0 | 8000 | 2.0183 | 4.3294 | 0.9444 | 4.3408 | 4.3611 |
| 2.0276 | 5.0 | 10000 | 2.0039 | 4.6694 | 0.9444 | 4.6264 | 4.6527 |
| 1.9119 | 6.0 | 12000 | 2.0139 | 4.9447 | 1.0675 | 4.8908 | 4.9633 |
| 1.8305 | 7.0 | 14000 | 2.0134 | 4.9385 | 1.1595 | 4.8774 | 4.9294 |
| 1.7669 | 8.0 | 16000 | 2.0253 | 4.2697 | 0.9667 | 4.2524 | 4.3167 |
| 1.7141 | 9.0 | 18000 | 2.0354 | 4.4527 | 0.9 | 4.448 | 4.4941 |
| 1.681 | 10.0 | 20000 | 2.0401 | 4.4311 | 0.8944 | 4.4294 | 4.4527 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
|