File size: 4,143 Bytes
e226049 | 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 85 86 87 88 89 90 91 92 93 94 | ---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-rouge-muhammad
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. -->
# flan-t5-rouge-muhammad
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Rouge1: 0.9614
- Rouge2: 0.6993
- Rougel: 0.9620
- Rougelsum: 0.9608
## 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: 0.0003
- 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.302 | 1.0 | 50 | 2.5839 | 0.0277 | 0.0 | 0.0266 | 0.0267 |
| 2.806 | 2.0 | 100 | 1.6441 | 0.0944 | 0.0367 | 0.0940 | 0.0952 |
| 1.3348 | 3.0 | 150 | 1.1077 | 0.1653 | 0.0429 | 0.1644 | 0.1650 |
| 1.7996 | 4.0 | 200 | 0.7027 | 0.2908 | 0.1621 | 0.2864 | 0.2898 |
| 0.7975 | 5.0 | 250 | 0.4608 | 0.4016 | 0.2158 | 0.3954 | 0.3971 |
| 0.3679 | 6.0 | 300 | 0.3462 | 0.4970 | 0.2975 | 0.4969 | 0.5016 |
| 0.8118 | 7.0 | 350 | 0.2211 | 0.6163 | 0.3819 | 0.6142 | 0.6161 |
| 0.4616 | 8.0 | 400 | 0.1314 | 0.7334 | 0.4850 | 0.7321 | 0.7343 |
| 0.4839 | 9.0 | 450 | 0.0681 | 0.8123 | 0.5500 | 0.8126 | 0.8130 |
| 0.0311 | 10.0 | 500 | 0.0677 | 0.8569 | 0.5984 | 0.8564 | 0.8554 |
| 0.4817 | 11.0 | 550 | 0.0445 | 0.8553 | 0.6003 | 0.8552 | 0.8563 |
| 0.3256 | 12.0 | 600 | 0.0502 | 0.8970 | 0.6382 | 0.8964 | 0.8972 |
| 0.2595 | 13.0 | 650 | 0.0243 | 0.9115 | 0.6440 | 0.9110 | 0.9110 |
| 0.0417 | 14.0 | 700 | 0.0209 | 0.9417 | 0.6744 | 0.9407 | 0.9414 |
| 0.0356 | 15.0 | 750 | 0.0110 | 0.9467 | 0.6840 | 0.9468 | 0.9449 |
| 0.0033 | 16.0 | 800 | 0.0131 | 0.9426 | 0.6752 | 0.9423 | 0.9407 |
| 0.0912 | 17.0 | 850 | 0.0043 | 0.9574 | 0.6933 | 0.9574 | 0.9564 |
| 0.1195 | 18.0 | 900 | 0.0031 | 0.9608 | 0.6986 | 0.9613 | 0.9602 |
| 0.0067 | 19.0 | 950 | 0.0026 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.1854 | 20.0 | 1000 | 0.0017 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0199 | 21.0 | 1050 | 0.0017 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0022 | 22.0 | 1100 | 0.0006 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0014 | 23.0 | 1150 | 0.0005 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0823 | 24.0 | 1200 | 0.0002 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0012 | 25.0 | 1250 | 0.0002 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.065 | 26.0 | 1300 | 0.0001 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0025 | 27.0 | 1350 | 0.0001 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0046 | 28.0 | 1400 | 0.0000 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.004 | 29.0 | 1450 | 0.0000 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
| 0.0011 | 30.0 | 1500 | 0.0000 | 0.9614 | 0.6993 | 0.9620 | 0.9608 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
|