File size: 2,118 Bytes
b532629 547e632 b532629 547e632 b532629 547e632 b532629 547e632 b532629 |
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-task1-dataset2
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-task1-dataset2
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: 0.5493
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.4035 | 1.0 | 500 | 0.9806 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.049 | 2.0 | 1000 | 0.7479 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8222 | 3.0 | 1500 | 0.6804 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.7272 | 4.0 | 2000 | 0.6246 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.6758 | 5.0 | 2500 | 0.5872 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.6367 | 6.0 | 3000 | 0.5728 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.6214 | 7.0 | 3500 | 0.5567 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.6107 | 8.0 | 4000 | 0.5493 | 0.0 | 0.0 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|