File size: 2,481 Bytes
be318ce |
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 |
---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- gazeta
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gazeta
type: gazeta
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 9.9348
---
<!-- 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-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the gazeta dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2573
- Rouge1: 9.9348
- Rouge2: 1.4701
- Rougel: 9.7352
- Rougelsum: 9.7173
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 5.0727 | 1.0 | 763 | 2.4238 | 9.9038 | 2.2835 | 9.5715 | 9.6056 |
| 3.4561 | 2.0 | 1526 | 2.3779 | 10.5328 | 2.1668 | 10.297 | 10.2517 |
| 3.2731 | 3.0 | 2289 | 2.3248 | 11.0603 | 2.3552 | 10.9513 | 10.9458 |
| 3.1629 | 4.0 | 3052 | 2.2993 | 9.6206 | 1.553 | 9.4704 | 9.4079 |
| 3.0912 | 5.0 | 3815 | 2.2779 | 9.9379 | 1.5493 | 9.7858 | 9.7129 |
| 3.0449 | 6.0 | 4578 | 2.2698 | 10.1558 | 1.5231 | 9.947 | 9.8629 |
| 3.0184 | 7.0 | 5341 | 2.2683 | 9.7056 | 1.5373 | 9.4965 | 9.3964 |
| 2.9987 | 8.0 | 6104 | 2.2573 | 9.9348 | 1.4701 | 9.7352 | 9.7173 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
|