File size: 3,086 Bytes
c15720e |
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 |
---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-text-sum-5
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-text-sum-5
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: 2.3673
- Rouge1: 21.51
- Rouge2: 6.94
- Rougel: 20.94
## 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: 0.0001
- train_batch_size: 11
- eval_batch_size: 11
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
| 4.5176 | 1.77 | 500 | 2.6172 | 16.23 | 5.35 | 16.14 |
| 3.073 | 3.55 | 1000 | 2.4755 | 17.77 | 5.53 | 17.67 |
| 2.8478 | 5.32 | 1500 | 2.4330 | 18.56 | 5.28 | 18.32 |
| 2.7152 | 7.09 | 2000 | 2.4423 | 18.31 | 5.1 | 18.14 |
| 2.6003 | 8.87 | 2500 | 2.3905 | 19.46 | 5.52 | 19.17 |
| 2.5218 | 10.64 | 3000 | 2.3660 | 19.58 | 5.93 | 19.07 |
| 2.4172 | 12.41 | 3500 | 2.3595 | 19.89 | 6.42 | 19.5 |
| 2.3841 | 14.18 | 4000 | 2.3564 | 20.38 | 6.67 | 19.99 |
| 2.3049 | 15.96 | 4500 | 2.3730 | 20.21 | 6.41 | 19.79 |
| 2.2596 | 17.73 | 5000 | 2.3532 | 20.27 | 6.38 | 19.95 |
| 2.2155 | 19.5 | 5500 | 2.3539 | 19.6 | 6.41 | 19.24 |
| 2.1657 | 21.28 | 6000 | 2.3511 | 21.13 | 6.19 | 20.79 |
| 2.1343 | 23.05 | 6500 | 2.3378 | 20.59 | 6.45 | 20.18 |
| 2.1032 | 24.82 | 7000 | 2.3510 | 19.91 | 6.28 | 19.6 |
| 2.068 | 26.6 | 7500 | 2.3452 | 19.37 | 6.11 | 19.1 |
| 2.0438 | 28.37 | 8000 | 2.3513 | 20.86 | 6.43 | 20.49 |
| 2.0191 | 30.14 | 8500 | 2.3673 | 21.51 | 6.94 | 20.94 |
| 2.0085 | 31.91 | 9000 | 2.3519 | 20.65 | 6.61 | 20.2 |
| 1.9797 | 33.69 | 9500 | 2.3728 | 21.01 | 6.33 | 20.6 |
| 1.9808 | 35.46 | 10000 | 2.3663 | 21.22 | 6.48 | 20.82 |
| 1.9605 | 37.23 | 10500 | 2.3581 | 20.45 | 6.41 | 20.06 |
| 1.9599 | 39.01 | 11000 | 2.3608 | 21.07 | 6.57 | 20.6 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
|