AbidHasan95
commited on
Commit
•
cc0e089
1
Parent(s):
276c369
update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,94 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
metrics:
|
6 |
+
- precision
|
7 |
+
- recall
|
8 |
+
- f1
|
9 |
+
- accuracy
|
10 |
+
model-index:
|
11 |
+
- name: movieHunt4-ner
|
12 |
+
results: []
|
13 |
+
---
|
14 |
+
|
15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
16 |
+
should probably proofread and complete it, then remove this comment. -->
|
17 |
+
|
18 |
+
# movieHunt4-ner
|
19 |
+
|
20 |
+
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
|
21 |
+
It achieves the following results on the evaluation set:
|
22 |
+
- Loss: 0.0005
|
23 |
+
- Precision: 1.0
|
24 |
+
- Recall: 1.0
|
25 |
+
- F1: 1.0
|
26 |
+
- Accuracy: 1.0
|
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: 2e-05
|
46 |
+
- train_batch_size: 32
|
47 |
+
- eval_batch_size: 32
|
48 |
+
- seed: 42
|
49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
50 |
+
- lr_scheduler_type: linear
|
51 |
+
- num_epochs: 30
|
52 |
+
|
53 |
+
### Training results
|
54 |
+
|
55 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
56 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
57 |
+
| No log | 1.0 | 48 | 0.0284 | 0.9959 | 0.9959 | 0.9959 | 0.9974 |
|
58 |
+
| No log | 2.0 | 96 | 0.0060 | 1.0 | 1.0 | 1.0 | 1.0 |
|
59 |
+
| No log | 3.0 | 144 | 0.0034 | 1.0 | 1.0 | 1.0 | 1.0 |
|
60 |
+
| No log | 4.0 | 192 | 0.0025 | 1.0 | 1.0 | 1.0 | 1.0 |
|
61 |
+
| No log | 5.0 | 240 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 |
|
62 |
+
| No log | 6.0 | 288 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
|
63 |
+
| No log | 7.0 | 336 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 |
|
64 |
+
| No log | 8.0 | 384 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 |
|
65 |
+
| No log | 9.0 | 432 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
|
66 |
+
| No log | 10.0 | 480 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 |
|
67 |
+
| 0.0168 | 11.0 | 528 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
|
68 |
+
| 0.0168 | 12.0 | 576 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
|
69 |
+
| 0.0168 | 13.0 | 624 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
|
70 |
+
| 0.0168 | 14.0 | 672 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
|
71 |
+
| 0.0168 | 15.0 | 720 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
|
72 |
+
| 0.0168 | 16.0 | 768 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
|
73 |
+
| 0.0168 | 17.0 | 816 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
|
74 |
+
| 0.0168 | 18.0 | 864 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
|
75 |
+
| 0.0168 | 19.0 | 912 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
|
76 |
+
| 0.0168 | 20.0 | 960 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
|
77 |
+
| 0.0014 | 21.0 | 1008 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
|
78 |
+
| 0.0014 | 22.0 | 1056 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
|
79 |
+
| 0.0014 | 23.0 | 1104 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
|
80 |
+
| 0.0014 | 24.0 | 1152 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
|
81 |
+
| 0.0014 | 25.0 | 1200 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
|
82 |
+
| 0.0014 | 26.0 | 1248 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
|
83 |
+
| 0.0014 | 27.0 | 1296 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
|
84 |
+
| 0.0014 | 28.0 | 1344 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
|
85 |
+
| 0.0014 | 29.0 | 1392 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
|
86 |
+
| 0.0014 | 30.0 | 1440 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
|
87 |
+
|
88 |
+
|
89 |
+
### Framework versions
|
90 |
+
|
91 |
+
- Transformers 4.21.0
|
92 |
+
- Pytorch 1.12.0+cu113
|
93 |
+
- Datasets 2.4.0
|
94 |
+
- Tokenizers 0.12.1
|