File size: 2,712 Bytes
c878443 |
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 |
---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-base-finetuned-test_30483_prefix_summarize
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-base-finetuned-test_30483_prefix_summarize
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3527
- Rouge1: 23.6141
- Rouge2: 7.1791
- Rougel: 16.0152
- Rougelsum: 21.8213
- Gen Len: 69.64
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 7.4668 | 1.25 | 500 | 2.6478 | 10.4597 | 4.2457 | 8.7184 | 9.8473 | 18.49 |
| 3.3231 | 2.5 | 1000 | 2.5146 | 17.7315 | 6.0795 | 13.5384 | 16.6839 | 40.55 |
| 3.0956 | 3.75 | 1500 | 2.4512 | 20.2871 | 6.4051 | 14.8508 | 18.8768 | 51.35 |
| 2.9928 | 5.0 | 2000 | 2.4180 | 21.4196 | 6.629 | 15.2607 | 20.1471 | 57.92 |
| 2.8802 | 6.25 | 2500 | 2.4030 | 21.7949 | 6.7926 | 15.2506 | 20.338 | 61.05 |
| 2.8243 | 7.5 | 3000 | 2.3856 | 21.7075 | 6.7397 | 15.0044 | 20.1744 | 61.19 |
| 2.7646 | 8.75 | 3500 | 2.3847 | 22.4137 | 6.7644 | 14.9987 | 20.7797 | 63.81 |
| 2.7096 | 10.0 | 4000 | 2.3691 | 22.3403 | 6.9812 | 15.5411 | 20.6166 | 62.79 |
| 2.6758 | 11.25 | 4500 | 2.3612 | 23.6542 | 7.2355 | 15.9979 | 21.9807 | 69.83 |
| 2.6579 | 12.5 | 5000 | 2.3556 | 23.7473 | 7.5446 | 16.0314 | 21.917 | 69.75 |
| 2.651 | 13.75 | 5500 | 2.3557 | 23.9711 | 7.5018 | 16.2033 | 22.2811 | 69.29 |
| 2.639 | 15.0 | 6000 | 2.3527 | 23.6141 | 7.1791 | 16.0152 | 21.8213 | 69.64 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3
|