update model card README.md
Browse files
README.md
CHANGED
@@ -2,6 +2,9 @@
|
|
2 |
license: apache-2.0
|
3 |
tags:
|
4 |
- generated_from_trainer
|
|
|
|
|
|
|
5 |
model-index:
|
6 |
- name: BT5153-kaggle-sentiment-model-3000-samples
|
7 |
results: []
|
@@ -13,6 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
|
|
13 |
# BT5153-kaggle-sentiment-model-3000-samples
|
14 |
|
15 |
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
|
|
|
|
|
|
|
|
|
16 |
|
17 |
## Model description
|
18 |
|
@@ -32,15 +39,32 @@ More information needed
|
|
32 |
|
33 |
The following hyperparameters were used during training:
|
34 |
- learning_rate: 2e-05
|
35 |
-
- train_batch_size:
|
36 |
-
- eval_batch_size:
|
37 |
- seed: 42
|
38 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
39 |
- lr_scheduler_type: linear
|
40 |
-
- num_epochs:
|
41 |
|
42 |
### Training results
|
43 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
44 |
|
45 |
|
46 |
### Framework versions
|
|
|
2 |
license: apache-2.0
|
3 |
tags:
|
4 |
- generated_from_trainer
|
5 |
+
metrics:
|
6 |
+
- accuracy
|
7 |
+
- f1
|
8 |
model-index:
|
9 |
- name: BT5153-kaggle-sentiment-model-3000-samples
|
10 |
results: []
|
|
|
16 |
# BT5153-kaggle-sentiment-model-3000-samples
|
17 |
|
18 |
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
|
19 |
+
It achieves the following results on the evaluation set:
|
20 |
+
- Loss: 0.6160
|
21 |
+
- Accuracy: 0.9270
|
22 |
+
- F1: 0.9288
|
23 |
|
24 |
## Model description
|
25 |
|
|
|
39 |
|
40 |
The following hyperparameters were used during training:
|
41 |
- learning_rate: 2e-05
|
42 |
+
- train_batch_size: 32
|
43 |
+
- eval_batch_size: 32
|
44 |
- seed: 42
|
45 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
46 |
- lr_scheduler_type: linear
|
47 |
+
- num_epochs: 15
|
48 |
|
49 |
### Training results
|
50 |
|
51 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|
52 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
|
53 |
+
| 0.2851 | 1.0 | 625 | 0.2058 | 0.9216 | 0.9231 |
|
54 |
+
| 0.1735 | 2.0 | 1250 | 0.2257 | 0.9244 | 0.9258 |
|
55 |
+
| 0.121 | 3.0 | 1875 | 0.2907 | 0.9232 | 0.9251 |
|
56 |
+
| 0.0525 | 4.0 | 2500 | 0.3607 | 0.9194 | 0.9219 |
|
57 |
+
| 0.0381 | 5.0 | 3125 | 0.4109 | 0.9216 | 0.9233 |
|
58 |
+
| 0.0257 | 6.0 | 3750 | 0.4142 | 0.9232 | 0.9244 |
|
59 |
+
| 0.0192 | 7.0 | 4375 | 0.4321 | 0.9230 | 0.9233 |
|
60 |
+
| 0.0126 | 8.0 | 5000 | 0.4745 | 0.9250 | 0.9278 |
|
61 |
+
| 0.01 | 9.0 | 5625 | 0.5053 | 0.9240 | 0.9246 |
|
62 |
+
| 0.0091 | 10.0 | 6250 | 0.5256 | 0.9240 | 0.9267 |
|
63 |
+
| 0.0062 | 11.0 | 6875 | 0.5798 | 0.9246 | 0.9255 |
|
64 |
+
| 0.0033 | 12.0 | 7500 | 0.5935 | 0.9242 | 0.9262 |
|
65 |
+
| 0.0019 | 13.0 | 8125 | 0.5891 | 0.9286 | 0.9303 |
|
66 |
+
| 0.0018 | 14.0 | 8750 | 0.6176 | 0.9266 | 0.9287 |
|
67 |
+
| 0.0001 | 15.0 | 9375 | 0.6160 | 0.9270 | 0.9288 |
|
68 |
|
69 |
|
70 |
### Framework versions
|