File size: 2,217 Bytes
282842b |
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 |
---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-icelandic-summary
results: []
---
<!-- 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. -->
# mt5-small-finetuned-icelandic-summary
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3019
- Rouge1: 24.5314
- Rouge2: 13.108
- Rougel: 21.8551
- Rougelsum: 22.5551
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 4.2489 | 1.0 | 1914 | 2.6014 | 17.9396 | 6.9767 | 15.0632 | 15.8916 |
| 3.0569 | 2.0 | 3828 | 2.4547 | 21.317 | 10.0433 | 18.6257 | 19.3813 |
| 2.8661 | 3.0 | 5742 | 2.3843 | 23.6521 | 12.2829 | 21.0046 | 21.7077 |
| 2.7543 | 4.0 | 7656 | 2.3642 | 23.8878 | 12.7041 | 21.3321 | 22.0867 |
| 2.682 | 5.0 | 9570 | 2.3379 | 24.2206 | 12.9703 | 21.6077 | 22.3493 |
| 2.6276 | 6.0 | 11484 | 2.2974 | 24.5156 | 13.1087 | 21.8464 | 22.5609 |
| 2.588 | 7.0 | 13398 | 2.3012 | 24.7653 | 13.3338 | 22.0548 | 22.762 |
| 2.5723 | 8.0 | 15312 | 2.3019 | 24.5314 | 13.108 | 21.8551 | 22.5551 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|