Text Classification
Transformers
Safetensors
modernbert
code
language-identification
multi-label
llm-guard
encoder
text-embeddings-inference
Instructions to use Accuknoxtechnologies/CodeLanguage-Encoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Accuknoxtechnologies/CodeLanguage-Encoder-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Accuknoxtechnologies/CodeLanguage-Encoder-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Accuknoxtechnologies/CodeLanguage-Encoder-v1") model = AutoModelForSequenceClassification.from_pretrained("Accuknoxtechnologies/CodeLanguage-Encoder-v1") - Notebooks
- Google Colab
- Kaggle
add eval metrics json
Browse files- eval_metrics.json +31 -30
eval_metrics.json
CHANGED
|
@@ -1,42 +1,43 @@
|
|
| 1 |
{
|
| 2 |
"n": 500,
|
| 3 |
"threshold": 0.5,
|
| 4 |
-
"
|
| 5 |
-
"
|
| 6 |
-
"
|
| 7 |
-
"
|
|
|
|
| 8 |
"per_language_f1": {
|
| 9 |
-
"Python": 0.
|
| 10 |
-
"JavaScript": 0.
|
| 11 |
-
"Java":
|
| 12 |
-
"C":
|
| 13 |
-
"C++": 0.
|
| 14 |
-
"C#": 0.
|
| 15 |
-
"Go": 0.
|
| 16 |
-
"Rust":
|
| 17 |
"Kotlin": 1.0,
|
| 18 |
-
"Swift": 0.
|
| 19 |
-
"Ruby": 0.
|
| 20 |
-
"R": 0.
|
| 21 |
-
"Scala": 0.
|
| 22 |
-
"Perl": 0.
|
| 23 |
-
"Lua": 0.
|
| 24 |
-
"Bash": 0.
|
| 25 |
-
"PowerShell": 0.
|
| 26 |
-
"Batch": 0.
|
| 27 |
-
"SQL":
|
| 28 |
-
"Dockerfile": 0.
|
| 29 |
-
"YAML": 0.
|
| 30 |
-
"Makefile": 0.
|
| 31 |
-
"Terraform": 0.
|
| 32 |
"AWK": 0.9259259259259259,
|
| 33 |
-
"jq": 0.
|
| 34 |
},
|
| 35 |
"latency_ms_per_example": {
|
| 36 |
-
"mean": 2.
|
| 37 |
-
"p95":
|
| 38 |
"device": "cuda:0"
|
| 39 |
},
|
| 40 |
"base_model": "jhu-clsp/mmBERT-base",
|
| 41 |
-
"epochs":
|
| 42 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"n": 500,
|
| 3 |
"threshold": 0.5,
|
| 4 |
+
"max_seq_length": 3072,
|
| 5 |
+
"is_valid_accuracy": 0.958,
|
| 6 |
+
"category_set_accuracy": 0.82,
|
| 7 |
+
"micro_f1": 0.8976234003656307,
|
| 8 |
+
"macro_f1": 0.8954906015550027,
|
| 9 |
"per_language_f1": {
|
| 10 |
+
"Python": 0.8627450980392157,
|
| 11 |
+
"JavaScript": 0.8163265306122449,
|
| 12 |
+
"Java": 0.9166666666666666,
|
| 13 |
+
"C": 0.8636363636363636,
|
| 14 |
+
"C++": 0.9361702127659575,
|
| 15 |
+
"C#": 0.926829268292683,
|
| 16 |
+
"Go": 0.918918918918919,
|
| 17 |
+
"Rust": 0.9811320754716981,
|
| 18 |
"Kotlin": 1.0,
|
| 19 |
+
"Swift": 0.9166666666666666,
|
| 20 |
+
"Ruby": 0.9,
|
| 21 |
+
"R": 0.9056603773584906,
|
| 22 |
+
"Scala": 0.7619047619047619,
|
| 23 |
+
"Perl": 0.8571428571428571,
|
| 24 |
+
"Lua": 0.8666666666666667,
|
| 25 |
+
"Bash": 0.7222222222222222,
|
| 26 |
+
"PowerShell": 0.8333333333333334,
|
| 27 |
+
"Batch": 0.9019607843137255,
|
| 28 |
+
"SQL": 0.9803921568627451,
|
| 29 |
+
"Dockerfile": 0.9767441860465116,
|
| 30 |
+
"YAML": 0.9545454545454546,
|
| 31 |
+
"Makefile": 0.8780487804878049,
|
| 32 |
+
"Terraform": 0.8947368421052632,
|
| 33 |
"AWK": 0.9259259259259259,
|
| 34 |
+
"jq": 0.8888888888888888
|
| 35 |
},
|
| 36 |
"latency_ms_per_example": {
|
| 37 |
+
"mean": 2.3932456970214844,
|
| 38 |
+
"p95": 3.833106905221939,
|
| 39 |
"device": "cuda:0"
|
| 40 |
},
|
| 41 |
"base_model": "jhu-clsp/mmBERT-base",
|
| 42 |
+
"epochs": 2
|
| 43 |
}
|