update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- summarization
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
datasets:
|
| 7 |
+
- cnn_dailymail
|
| 8 |
+
model-index:
|
| 9 |
+
- name: t5-base-finetuned-summarization-cnn-ver2
|
| 10 |
+
results: []
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 14 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 15 |
+
|
| 16 |
+
# t5-base-finetuned-summarization-cnn-ver2
|
| 17 |
+
|
| 18 |
+
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the cnn_dailymail dataset.
|
| 19 |
+
It achieves the following results on the evaluation set:
|
| 20 |
+
- Loss: 1.7601
|
| 21 |
+
- Bertscore-mean-precision: 0.8926
|
| 22 |
+
- Bertscore-mean-recall: 0.8628
|
| 23 |
+
- Bertscore-mean-f1: 0.8772
|
| 24 |
+
- Bertscore-median-precision: 0.8906
|
| 25 |
+
- Bertscore-median-recall: 0.8600
|
| 26 |
+
- Bertscore-median-f1: 0.8751
|
| 27 |
+
|
| 28 |
+
## Model description
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Intended uses & limitations
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training and evaluation data
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training procedure
|
| 41 |
+
|
| 42 |
+
### Training hyperparameters
|
| 43 |
+
|
| 44 |
+
The following hyperparameters were used during training:
|
| 45 |
+
- learning_rate: 5e-05
|
| 46 |
+
- train_batch_size: 1
|
| 47 |
+
- eval_batch_size: 1
|
| 48 |
+
- seed: 42
|
| 49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 50 |
+
- lr_scheduler_type: linear
|
| 51 |
+
- num_epochs: 3
|
| 52 |
+
|
| 53 |
+
### Training results
|
| 54 |
+
|
| 55 |
+
| Training Loss | Epoch | Step | Validation Loss | Bertscore-mean-precision | Bertscore-mean-recall | Bertscore-mean-f1 | Bertscore-median-precision | Bertscore-median-recall | Bertscore-median-f1 |
|
| 56 |
+
|:-------------:|:-----:|:-----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:--------------------------:|:-----------------------:|:-------------------:|
|
| 57 |
+
| 1.4581 | 1.0 | 5742 | 1.6800 | 0.8904 | 0.8615 | 0.8755 | 0.8887 | 0.8597 | 0.8737 |
|
| 58 |
+
| 1.2356 | 2.0 | 11484 | 1.7274 | 0.8924 | 0.8626 | 0.8771 | 0.8911 | 0.8607 | 0.8753 |
|
| 59 |
+
| 1.1073 | 3.0 | 17226 | 1.7601 | 0.8926 | 0.8628 | 0.8772 | 0.8906 | 0.8600 | 0.8751 |
|
| 60 |
+
|
| 61 |
+
|
| 62 |
+
### Framework versions
|
| 63 |
+
|
| 64 |
+
- Transformers 4.24.0
|
| 65 |
+
- Pytorch 1.12.1+cu113
|
| 66 |
+
- Datasets 2.7.1
|
| 67 |
+
- Tokenizers 0.13.2
|