sohamtiwari3120
commited on
Commit
•
467a5d0
1
Parent(s):
1e9f53f
update model card README.md
Browse files
README.md
CHANGED
@@ -16,18 +16,18 @@ should probably proofread and complete it, then remove this comment. -->
|
|
16 |
|
17 |
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the generator dataset.
|
18 |
It achieves the following results on the evaluation set:
|
19 |
-
- Loss: 1.
|
20 |
-
- Overall Precision: 0.
|
21 |
-
- Overall Recall: 0.
|
22 |
-
- Overall F1: 0.
|
23 |
-
- Overall Accuracy: 0.
|
24 |
-
- Datasetname F1: 0.
|
25 |
-
- Hyperparametername F1: 0.
|
26 |
-
- Hyperparametervalue F1: 0.
|
27 |
-
- Methodname F1: 0.
|
28 |
-
- Metricname F1: 0.
|
29 |
-
- Metricvalue F1: 0.
|
30 |
-
- Taskname F1: 0.
|
31 |
|
32 |
## Model description
|
33 |
|
@@ -46,7 +46,7 @@ More information needed
|
|
46 |
### Training hyperparameters
|
47 |
|
48 |
The following hyperparameters were used during training:
|
49 |
-
- learning_rate:
|
50 |
- train_batch_size: 4
|
51 |
- eval_batch_size: 8
|
52 |
- seed: 42
|
@@ -58,12 +58,13 @@ The following hyperparameters were used during training:
|
|
58 |
|
59 |
| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Datasetname F1 | Hyperparametername F1 | Hyperparametervalue F1 | Methodname F1 | Metricname F1 | Metricvalue F1 | Taskname F1 |
|
60 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:---------------------:|:----------------------:|:-------------:|:-------------:|:--------------:|:-----------:|
|
61 |
-
| No log | 1.0 | 141 | 1.
|
62 |
-
| No log | 2.0 | 282 |
|
63 |
-
| No log | 3.0 | 423 | 1.
|
64 |
-
|
|
65 |
-
|
|
66 |
-
|
|
|
|
67 |
|
68 |
|
69 |
### Framework versions
|
|
|
16 |
|
17 |
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the generator dataset.
|
18 |
It achieves the following results on the evaluation set:
|
19 |
+
- Loss: 1.9895
|
20 |
+
- Overall Precision: 0.5201
|
21 |
+
- Overall Recall: 0.3319
|
22 |
+
- Overall F1: 0.4052
|
23 |
+
- Overall Accuracy: 0.9326
|
24 |
+
- Datasetname F1: 0.4952
|
25 |
+
- Hyperparametername F1: 0.48
|
26 |
+
- Hyperparametervalue F1: 0.5
|
27 |
+
- Methodname F1: 0.3933
|
28 |
+
- Metricname F1: 0.2488
|
29 |
+
- Metricvalue F1: 0.2456
|
30 |
+
- Taskname F1: 0.6393
|
31 |
|
32 |
## Model description
|
33 |
|
|
|
46 |
### Training hyperparameters
|
47 |
|
48 |
The following hyperparameters were used during training:
|
49 |
+
- learning_rate: 3e-05
|
50 |
- train_batch_size: 4
|
51 |
- eval_batch_size: 8
|
52 |
- seed: 42
|
|
|
58 |
|
59 |
| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Datasetname F1 | Hyperparametername F1 | Hyperparametervalue F1 | Methodname F1 | Metricname F1 | Metricvalue F1 | Taskname F1 |
|
60 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:---------------------:|:----------------------:|:-------------:|:-------------:|:--------------:|:-----------:|
|
61 |
+
| No log | 1.0 | 141 | 1.2556 | 0.2784 | 0.1520 | 0.1967 | 0.9212 | 0.0 | 0.3478 | 0.2581 | 0.3750 | 0.0 | 0.0 | 0.0556 |
|
62 |
+
| No log | 2.0 | 282 | 0.8945 | 0.3020 | 0.5096 | 0.3793 | 0.9088 | 0.5 | 0.1538 | 0.2778 | 0.3540 | 0.4566 | 0.0896 | 0.3756 |
|
63 |
+
| No log | 3.0 | 423 | 1.0233 | 0.3702 | 0.4518 | 0.4069 | 0.9268 | 0.4211 | 0.2647 | 0.3333 | 0.3529 | 0.4658 | 0.1613 | 0.5270 |
|
64 |
+
| 0.6352 | 4.0 | 564 | 1.1734 | 0.4316 | 0.4390 | 0.4352 | 0.9310 | 0.4854 | 0.3462 | 0.3415 | 0.4352 | 0.4269 | 0.2295 | 0.5827 |
|
65 |
+
| 0.6352 | 5.0 | 705 | 1.3147 | 0.4840 | 0.4540 | 0.4685 | 0.9390 | 0.5143 | 0.5 | 0.625 | 0.5739 | 0.3495 | 0.2333 | 0.5865 |
|
66 |
+
| 0.6352 | 6.0 | 846 | 2.1441 | 0.5618 | 0.3405 | 0.4240 | 0.9373 | 0.5185 | 0.5581 | 0.6061 | 0.4898 | 0.2365 | 0.1071 | 0.6126 |
|
67 |
+
| 0.6352 | 7.0 | 987 | 1.9895 | 0.5201 | 0.3319 | 0.4052 | 0.9326 | 0.4952 | 0.48 | 0.5 | 0.3933 | 0.2488 | 0.2456 | 0.6393 |
|
68 |
|
69 |
|
70 |
### Framework versions
|