update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,73 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
metrics:
|
6 |
+
- rouge
|
7 |
+
model-index:
|
8 |
+
- name: t5-small-science-papers-NIPS
|
9 |
+
results: []
|
10 |
+
---
|
11 |
+
|
12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
13 |
+
should probably proofread and complete it, then remove this comment. -->
|
14 |
+
|
15 |
+
# t5-small-science-papers-NIPS
|
16 |
+
|
17 |
+
This model is a fine-tuned version of [Dagar/t5-small-science-papers](https://huggingface.co/Dagar/t5-small-science-papers) on the None dataset.
|
18 |
+
It achieves the following results on the evaluation set:
|
19 |
+
- Loss: 4.7566
|
20 |
+
- Rouge1: 15.7066
|
21 |
+
- Rouge2: 2.5654
|
22 |
+
- Rougel: 11.4679
|
23 |
+
- Rougelsum: 14.4017
|
24 |
+
- Gen Len: 19.0
|
25 |
+
|
26 |
+
## Model description
|
27 |
+
|
28 |
+
More information needed
|
29 |
+
|
30 |
+
## Intended uses & limitations
|
31 |
+
|
32 |
+
More information needed
|
33 |
+
|
34 |
+
## Training and evaluation data
|
35 |
+
|
36 |
+
More information needed
|
37 |
+
|
38 |
+
## Training procedure
|
39 |
+
|
40 |
+
### Training hyperparameters
|
41 |
+
|
42 |
+
The following hyperparameters were used during training:
|
43 |
+
- learning_rate: 2e-05
|
44 |
+
- train_batch_size: 16
|
45 |
+
- eval_batch_size: 16
|
46 |
+
- seed: 42
|
47 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
48 |
+
- lr_scheduler_type: linear
|
49 |
+
- num_epochs: 10
|
50 |
+
- mixed_precision_training: Native AMP
|
51 |
+
|
52 |
+
### Training results
|
53 |
+
|
54 |
+
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|
55 |
+
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
|
56 |
+
| No log | 1.0 | 318 | 5.1856 | 13.7172 | 2.0644 | 10.2189 | 12.838 | 19.0 |
|
57 |
+
| 5.4522 | 2.0 | 636 | 5.0383 | 15.6211 | 2.1808 | 11.3561 | 14.3054 | 19.0 |
|
58 |
+
| 5.4522 | 3.0 | 954 | 4.9486 | 15.1659 | 2.3308 | 11.1052 | 13.9456 | 19.0 |
|
59 |
+
| 5.1254 | 4.0 | 1272 | 4.8851 | 15.716 | 2.4099 | 11.4954 | 14.5099 | 19.0 |
|
60 |
+
| 4.9794 | 5.0 | 1590 | 4.8456 | 15.5507 | 2.4267 | 11.3867 | 14.3237 | 19.0 |
|
61 |
+
| 4.9794 | 6.0 | 1908 | 4.8073 | 15.8406 | 2.4254 | 11.6878 | 14.6154 | 19.0 |
|
62 |
+
| 4.8823 | 7.0 | 2226 | 4.7872 | 15.5554 | 2.4637 | 11.3401 | 14.3183 | 19.0 |
|
63 |
+
| 4.8338 | 8.0 | 2544 | 4.7680 | 15.4783 | 2.4888 | 11.3364 | 14.2031 | 19.0 |
|
64 |
+
| 4.8338 | 9.0 | 2862 | 4.7621 | 15.958 | 2.5662 | 11.6139 | 14.6576 | 19.0 |
|
65 |
+
| 4.7838 | 10.0 | 3180 | 4.7566 | 15.7066 | 2.5654 | 11.4679 | 14.4017 | 19.0 |
|
66 |
+
|
67 |
+
|
68 |
+
### Framework versions
|
69 |
+
|
70 |
+
- Transformers 4.24.0
|
71 |
+
- Pytorch 1.12.1+cu113
|
72 |
+
- Datasets 2.7.1
|
73 |
+
- Tokenizers 0.13.2
|