dipteshkanojia
commited on
Commit
·
c2e166e
1
Parent(s):
0df6679
update model card README.md
Browse files
README.md
CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
|
|
19 |
|
20 |
This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on an unknown dataset.
|
21 |
It achieves the following results on the evaluation set:
|
22 |
-
- Loss:
|
23 |
-
- Accuracy: 0.
|
24 |
-
- Precision: 0.
|
25 |
-
- Recall: 0.
|
26 |
-
- F1: 0.
|
27 |
|
28 |
## Model description
|
29 |
|
@@ -48,14 +48,17 @@ The following hyperparameters were used during training:
|
|
48 |
- seed: 43
|
49 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
50 |
- lr_scheduler_type: linear
|
51 |
-
- num_epochs:
|
52 |
|
53 |
### Training results
|
54 |
|
55 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|
56 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
|
57 |
-
| 1.
|
58 |
-
| 1.
|
|
|
|
|
|
|
59 |
|
60 |
|
61 |
### Framework versions
|
|
|
19 |
|
20 |
This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on an unknown dataset.
|
21 |
It achieves the following results on the evaluation set:
|
22 |
+
- Loss: 0.9997
|
23 |
+
- Accuracy: 0.5620
|
24 |
+
- Precision: 0.5591
|
25 |
+
- Recall: 0.5203
|
26 |
+
- F1: 0.5078
|
27 |
|
28 |
## Model description
|
29 |
|
|
|
48 |
- seed: 43
|
49 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
50 |
- lr_scheduler_type: linear
|
51 |
+
- num_epochs: 20
|
52 |
|
53 |
### Training results
|
54 |
|
55 |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|
56 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
|
57 |
+
| 1.0673 | 3.99 | 926 | 1.0361 | 0.4142 | 0.4092 | 0.3851 | 0.2750 |
|
58 |
+
| 1.0144 | 7.98 | 1852 | 1.0147 | 0.5146 | 0.5851 | 0.4714 | 0.4184 |
|
59 |
+
| 0.9882 | 11.97 | 2778 | 1.0045 | 0.5599 | 0.5728 | 0.5191 | 0.5047 |
|
60 |
+
| 0.9699 | 15.97 | 3704 | 1.0004 | 0.5642 | 0.5620 | 0.5264 | 0.5193 |
|
61 |
+
| 0.9591 | 19.96 | 4630 | 0.9997 | 0.5620 | 0.5591 | 0.5203 | 0.5078 |
|
62 |
|
63 |
|
64 |
### Framework versions
|