File size: 2,297 Bytes
c8002d3 9655d04 c8002d3 f892ab0 c8002d3 9655d04 c8002d3 f892ab0 c8002d3 |
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 |
---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: AI_Chaperone
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. -->
# AI_Chaperone
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: 1.3785
- Rouge1: 0.1505
- Rouge2: 0.0376
- Rougel: 0.1461
- Rougelsum: 0.1475
## 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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log | 1.0 | 380 | 0.8274 | 0.1131 | 0.0226 | 0.1105 | 0.1109 |
| 1.2345 | 2.0 | 760 | 0.8217 | 0.1146 | 0.0229 | 0.1124 | 0.1133 |
| 0.6137 | 3.0 | 1140 | 0.8487 | 0.1316 | 0.0277 | 0.1260 | 0.1277 |
| 0.4624 | 4.0 | 1520 | 0.9179 | 0.1382 | 0.0286 | 0.1333 | 0.1343 |
| 0.4624 | 5.0 | 1900 | 0.9816 | 0.1430 | 0.0288 | 0.1371 | 0.1391 |
| 0.3444 | 6.0 | 2280 | 1.0601 | 0.1545 | 0.0362 | 0.1510 | 0.1517 |
| 0.2751 | 7.0 | 2660 | 1.1619 | 0.1520 | 0.0335 | 0.1481 | 0.1483 |
| 0.2223 | 8.0 | 3040 | 1.2493 | 0.1515 | 0.0349 | 0.1472 | 0.1475 |
| 0.2223 | 9.0 | 3420 | 1.3379 | 0.1500 | 0.0381 | 0.1451 | 0.1464 |
| 0.1844 | 10.0 | 3800 | 1.3785 | 0.1505 | 0.0376 | 0.1461 | 0.1475 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|