theojolliffe
commited on
Commit
•
9570f2d
1
Parent(s):
ba0e056
update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,71 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
metrics:
|
6 |
+
- rouge
|
7 |
+
model-index:
|
8 |
+
- name: bart-large-cnn-finetuned-roundup-3-8
|
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 |
+
# bart-large-cnn-finetuned-roundup-3-8
|
16 |
+
|
17 |
+
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
|
18 |
+
It achieves the following results on the evaluation set:
|
19 |
+
- Loss: 1.4132
|
20 |
+
- Rouge1: 49.6606
|
21 |
+
- Rouge2: 28.4044
|
22 |
+
- Rougel: 31.5419
|
23 |
+
- Rougelsum: 46.2463
|
24 |
+
- Gen Len: 142.0
|
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: 2
|
45 |
+
- eval_batch_size: 2
|
46 |
+
- seed: 42
|
47 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
48 |
+
- lr_scheduler_type: linear
|
49 |
+
- num_epochs: 8
|
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 | 258 | 1.2686 | 48.8513 | 28.7007 | 31.1199 | 45.7318 | 142.0 |
|
57 |
+
| 1.1738 | 2.0 | 516 | 1.1884 | 49.8072 | 28.9817 | 31.3611 | 46.9639 | 141.6875 |
|
58 |
+
| 1.1738 | 3.0 | 774 | 1.1970 | 49.3865 | 28.3426 | 30.0945 | 46.4681 | 141.3438 |
|
59 |
+
| 0.7069 | 4.0 | 1032 | 1.1984 | 50.6743 | 29.4728 | 31.5364 | 47.989 | 141.7188 |
|
60 |
+
| 0.7069 | 5.0 | 1290 | 1.2494 | 49.4461 | 28.9295 | 31.0334 | 46.6611 | 142.0 |
|
61 |
+
| 0.4618 | 6.0 | 1548 | 1.2954 | 50.6789 | 30.2783 | 32.1932 | 47.5929 | 142.0 |
|
62 |
+
| 0.4618 | 7.0 | 1806 | 1.3638 | 49.9476 | 30.223 | 32.4346 | 46.7383 | 142.0 |
|
63 |
+
| 0.3293 | 8.0 | 2064 | 1.4132 | 49.6606 | 28.4044 | 31.5419 | 46.2463 | 142.0 |
|
64 |
+
|
65 |
+
|
66 |
+
### Framework versions
|
67 |
+
|
68 |
+
- Transformers 4.18.0
|
69 |
+
- Pytorch 1.11.0+cu113
|
70 |
+
- Datasets 2.1.0
|
71 |
+
- Tokenizers 0.12.1
|