File size: 2,157 Bytes
ea0f421 b21a021 ea0f421 b21a021 ea0f421 |
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 |
---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
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-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2891
- Rouge1: 15.35
- Rouge2: 6.4925
- Rougel: 14.8921
- Rougelsum: 14.6312
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 7.0622 | 1.0 | 1276 | 3.5617 | 13.2417 | 4.8928 | 12.8258 | 12.8078 |
| 4.0768 | 2.0 | 2552 | 3.4329 | 14.5681 | 6.4922 | 14.0621 | 13.9709 |
| 3.7736 | 3.0 | 3828 | 3.3393 | 15.1942 | 6.5262 | 14.7138 | 14.6049 |
| 3.5951 | 4.0 | 5104 | 3.3122 | 14.8813 | 6.2962 | 14.507 | 14.3477 |
| 3.477 | 5.0 | 6380 | 3.2991 | 15.0992 | 6.3888 | 14.8397 | 14.5606 |
| 3.4084 | 6.0 | 7656 | 3.3035 | 15.1897 | 6.2292 | 14.6686 | 14.4488 |
| 3.3661 | 7.0 | 8932 | 3.2959 | 15.3489 | 6.5702 | 14.9211 | 14.701 |
| 3.3457 | 8.0 | 10208 | 3.2891 | 15.35 | 6.4925 | 14.8921 | 14.6312 |
### Framework versions
- Transformers 4.19.1
- Pytorch 1.7.0
- Datasets 2.2.1
- Tokenizers 0.12.1
|