Model save
Browse files
README.md
CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
|
|
20 |
|
21 |
This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset.
|
22 |
It achieves the following results on the evaluation set:
|
23 |
-
- Loss: 0.
|
24 |
-
- F1: 0
|
25 |
-
- Accuracy: 0
|
26 |
-
- Precision: 0
|
27 |
-
- Recall: 0
|
28 |
|
29 |
## Model description
|
30 |
|
@@ -44,8 +44,8 @@ More information needed
|
|
44 |
|
45 |
The following hyperparameters were used during training:
|
46 |
- learning_rate: 0.0003
|
47 |
-
- train_batch_size:
|
48 |
-
- eval_batch_size:
|
49 |
- seed: 2024
|
50 |
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
51 |
- lr_scheduler_type: cosine
|
@@ -57,8 +57,8 @@ The following hyperparameters were used during training:
|
|
57 |
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
|
58 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
|
59 |
| No log | 0 | 0 | 0.6985 | 0.3223 | 0.49 | 0.2401 | 0.49 |
|
60 |
-
| 0.
|
61 |
-
| 0.
|
62 |
|
63 |
|
64 |
### Framework versions
|
|
|
20 |
|
21 |
This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset.
|
22 |
It achieves the following results on the evaluation set:
|
23 |
+
- Loss: 0.0041
|
24 |
+
- F1: 1.0
|
25 |
+
- Accuracy: 1.0
|
26 |
+
- Precision: 1.0
|
27 |
+
- Recall: 1.0
|
28 |
|
29 |
## Model description
|
30 |
|
|
|
44 |
|
45 |
The following hyperparameters were used during training:
|
46 |
- learning_rate: 0.0003
|
47 |
+
- train_batch_size: 320
|
48 |
+
- eval_batch_size: 320
|
49 |
- seed: 2024
|
50 |
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
51 |
- lr_scheduler_type: cosine
|
|
|
57 |
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
|
58 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
|
59 |
| No log | 0 | 0 | 0.6985 | 0.3223 | 0.49 | 0.2401 | 0.49 |
|
60 |
+
| 0.0001 | 12.5 | 50 | 0.0044 | 1.0 | 1.0 | 1.0 | 1.0 |
|
61 |
+
| 0.0001 | 25.0 | 100 | 0.0041 | 1.0 | 1.0 | 1.0 | 1.0 |
|
62 |
|
63 |
|
64 |
### Framework versions
|