File size: 2,500 Bytes
490e55d |
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 |
---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model_36
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. -->
# my_awesome_billsum_model_36
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: 0.4601
- Rouge1: 0.9721
- Rouge2: 0.8819
- Rougel: 0.9256
- Rougelsum: 0.9271
- Gen Len: 4.9167
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 12 | 1.9874 | 0.4145 | 0.2913 | 0.3883 | 0.3891 | 17.6042 |
| No log | 2.0 | 24 | 1.4300 | 0.4322 | 0.3091 | 0.4061 | 0.4068 | 17.0833 |
| No log | 3.0 | 36 | 0.9451 | 0.5076 | 0.3886 | 0.4814 | 0.48 | 14.75 |
| No log | 4.0 | 48 | 0.6345 | 0.8401 | 0.7297 | 0.7858 | 0.7884 | 7.625 |
| No log | 5.0 | 60 | 0.5226 | 0.9591 | 0.8586 | 0.8998 | 0.9042 | 5.125 |
| No log | 6.0 | 72 | 0.4907 | 0.9701 | 0.8736 | 0.9129 | 0.9167 | 4.8958 |
| No log | 7.0 | 84 | 0.4783 | 0.9701 | 0.8736 | 0.9129 | 0.9167 | 4.8958 |
| No log | 8.0 | 96 | 0.4697 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 |
| No log | 9.0 | 108 | 0.4627 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 |
| No log | 10.0 | 120 | 0.4601 | 0.9721 | 0.8819 | 0.9256 | 0.9271 | 4.9167 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|