AdnanRiaz107
/

CBertbase-APPS10k

@@ -1,199 +1,78 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+base_model: microsoft/codebert-base
+tags:
+- generated_from_trainer
+model-index:
+- name: CBertbase-APPS10k
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# CBertbase-APPS10k
+This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0001
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- training_steps: 10000
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 1.4626        | 0.05  | 500   | 0.0390          |
+| 0.0215        | 0.1   | 1000  | 0.0065          |
+| 0.0096        | 0.15  | 1500  | 0.0018          |
+| 0.0022        | 0.2   | 2000  | 0.0009          |
+| 0.0023        | 0.25  | 2500  | 0.0003          |
+| 0.0011        | 0.3   | 3000  | 0.0004          |
+| 0.0011        | 0.35  | 3500  | 0.0002          |
+| 0.0016        | 0.4   | 4000  | 0.0002          |
+| 0.0006        | 0.45  | 4500  | 0.0001          |
+| 0.0004        | 0.5   | 5000  | 0.0001          |
+| 0.0002        | 0.55  | 5500  | 0.0001          |
+| 0.0002        | 0.6   | 6000  | 0.0001          |
+| 0.0003        | 0.65  | 6500  | 0.0001          |
+| 0.0001        | 0.7   | 7000  | 0.0001          |
+| 0.0001        | 0.75  | 7500  | 0.0001          |
+| 0.0001        | 0.8   | 8000  | 0.0001          |
+| 0.0001        | 0.85  | 8500  | 0.0001          |
+| 0.0001        | 0.9   | 9000  | 0.0001          |
+| 0.0001        | 0.95  | 9500  | 0.0001          |
+| 0.0001        | 1.0   | 10000 | 0.0001          |
+### Framework versions
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json CHANGED Viewed

@@ -1,7 +1,7 @@
 {
   "_name_or_path": "microsoft/codebert-base",
   "architectures": [
-    "RobertaModel"
   ],
   "attention_probs_dropout_prob": 0.1,
   "bos_token_id": 0,
@@ -20,8 +20,9 @@
   "output_past": true,
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "transformers_version": "4.38.2",
   "type_vocab_size": 1,
-  "use_cache": true,
   "vocab_size": 50265
 }

 {
   "_name_or_path": "microsoft/codebert-base",
   "architectures": [
+    "RobertaForCausalLM"
   ],
   "attention_probs_dropout_prob": 0.1,
   "bos_token_id": 0,
   "output_past": true,
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
   "transformers_version": "4.38.2",
   "type_vocab_size": 1,
+  "use_cache": false,
   "vocab_size": 50265
 }