File size: 2,171 Bytes
62ad8a2 |
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
base_model: google/mt5-small
tags:
- 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5259
- Rouge1: 36.6783
- Rouge2: 8.5304
- Rougel: 26.4419
- Rougelsum: 26.6455
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.833 | 1.0 | 250 | 2.6792 | 31.8471 | 7.6517 | 22.5413 | 22.6222 |
| 3.5861 | 2.0 | 500 | 2.6408 | 36.8204 | 8.641 | 26.7687 | 26.9114 |
| 3.411 | 3.0 | 750 | 2.6037 | 36.2502 | 7.9975 | 26.3962 | 26.502 |
| 3.29 | 4.0 | 1000 | 2.5673 | 36.7784 | 8.4415 | 26.7726 | 26.9248 |
| 3.2199 | 5.0 | 1250 | 2.5568 | 36.8812 | 8.7419 | 26.7704 | 26.8682 |
| 3.1628 | 6.0 | 1500 | 2.5280 | 37.1871 | 8.8604 | 26.9372 | 27.0992 |
| 3.1292 | 7.0 | 1750 | 2.5265 | 36.6801 | 8.5876 | 26.4392 | 26.5908 |
| 3.1129 | 8.0 | 2000 | 2.5259 | 36.6783 | 8.5304 | 26.4419 | 26.6455 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|