File size: 2,125 Bytes
1146a54 c3b0f28 1146a54 c3b0f28 1146a54 c3b0f28 1146a54 c3b0f28 1146a54 c3b0f28 1146a54 c3b0f28 1146a54 c3b0f28 |
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 |
---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: senate_bills_summary_model
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/cheaptrix/MTSUFall2024SoftwareEngineering/runs/rigak20g)
# senate_bills_summary_model
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co./google-t5/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9849
- Rouge1: 0.2462
- Rouge2: 0.1934
- Rougel: 0.2389
- Rougelsum: 0.2389
- Gen Len: 18.9981
## 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: 14
- eval_batch_size: 14
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.7477 | 1.0 | 749 | 2.1012 | 0.2474 | 0.192 | 0.2397 | 0.2396 | 18.9992 |
| 2.3215 | 2.0 | 1498 | 2.0257 | 0.2464 | 0.1931 | 0.2391 | 0.239 | 18.9992 |
| 2.2304 | 3.0 | 2247 | 1.9963 | 0.2459 | 0.1933 | 0.2386 | 0.2386 | 18.9989 |
| 2.194 | 4.0 | 2996 | 1.9849 | 0.2462 | 0.1934 | 0.2389 | 0.2389 | 18.9981 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
|