File size: 2,141 Bytes
843024b |
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 |
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: 7epochisdabest
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. -->
# 7epochisdabest
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6723
- Rouge1: 0.1892
- Rouge2: 0.0723
- Rougel: 0.1517
- Rougelsum: 0.1515
- Gen Len: 19.0
## 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: 5e-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: 7
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.0939 | 1.0 | 1370 | 2.7942 | 0.1877 | 0.0727 | 0.1506 | 0.1505 | 18.894 |
| 2.9829 | 2.0 | 2740 | 2.7420 | 0.1901 | 0.0734 | 0.1523 | 0.152 | 19.0 |
| 2.9343 | 3.0 | 4110 | 2.7119 | 0.1898 | 0.0733 | 0.1522 | 0.1521 | 19.0 |
| 2.9013 | 4.0 | 5480 | 2.6937 | 0.1891 | 0.0723 | 0.1514 | 0.1512 | 19.0 |
| 2.8908 | 5.0 | 6850 | 2.6799 | 0.1895 | 0.0723 | 0.1515 | 0.1513 | 19.0 |
| 2.8676 | 6.0 | 8220 | 2.6749 | 0.1889 | 0.0722 | 0.1518 | 0.1517 | 19.0 |
| 2.8433 | 7.0 | 9590 | 2.6723 | 0.1892 | 0.0723 | 0.1517 | 0.1515 | 19.0 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|