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CBertbase-mlm-APPS10k

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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
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  ---
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- # Model Card for Model ID
 
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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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- ### Model Description
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- ### Direct Use
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- [More Information Needed]
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- ### Downstream Use [optional]
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- ## Bias, Risks, and Limitations
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- ### Recommendations
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- ## Training Details
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- ### Training Data
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- ### Training Procedure
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- ## Evaluation
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- #### Factors
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- #### Metrics
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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  ---
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+ base_model: microsoft/codebert-base-mlm
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: CBertbase-mlm-APPS10k
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+ results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+ # CBertbase-mlm-APPS10k
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+ This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0911
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+ ## Model description
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+ More information needed
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+ ## Intended uses & limitations
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+ More information needed
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+ ## Training and evaluation data
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+ More information needed
 
 
 
 
 
 
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+ ## Training procedure
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 100
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+ - training_steps: 10000
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 2.1352 | 0.05 | 500 | 1.8774 |
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+ | 1.1754 | 0.1 | 1000 | 1.4835 |
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+ | 1.4127 | 0.15 | 1500 | 1.4475 |
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+ | 1.0497 | 0.2 | 2000 | 1.3342 |
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+ | 1.0403 | 0.25 | 2500 | 1.2589 |
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+ | 1.0754 | 0.3 | 3000 | 1.2174 |
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+ | 0.8836 | 0.35 | 3500 | 1.2265 |
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+ | 0.95 | 0.4 | 4000 | 1.1931 |
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+ | 1.0324 | 0.45 | 4500 | 1.1729 |
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+ | 1.0296 | 0.5 | 5000 | 1.1462 |
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+ | 0.886 | 0.55 | 5500 | 1.1364 |
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+ | 0.9352 | 0.6 | 6000 | 1.1201 |
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+ | 1.0547 | 0.65 | 6500 | 1.1481 |
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+ | 0.8277 | 0.7 | 7000 | 1.1128 |
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+ | 0.8685 | 0.75 | 7500 | 1.1153 |
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+ | 0.9277 | 0.8 | 8000 | 1.1194 |
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+ | 0.8111 | 0.85 | 8500 | 1.0975 |
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+ | 0.9345 | 0.9 | 9000 | 1.0913 |
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+ | 0.9166 | 0.95 | 9500 | 1.0904 |
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+ | 0.952 | 1.0 | 10000 | 1.0911 |
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+ ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
config.json CHANGED
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  {
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  "_name_or_path": "microsoft/codebert-base-mlm",
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  "architectures": [
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- "RobertaForMaskedLM"
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  ],
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  "attention_probs_dropout_prob": 0.1,
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  "bos_token_id": 0,
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  "hidden_size": 768,
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
 
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  "layer_norm_eps": 1e-05,
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  "max_position_embeddings": 514,
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  "model_type": "roberta",
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  "output_past": true,
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  "pad_token_id": 1,
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  "position_embedding_type": "absolute",
 
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  "transformers_version": "4.38.2",
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  "type_vocab_size": 1,
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- "use_cache": true,
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  "vocab_size": 50265
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  }
 
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  {
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  "_name_or_path": "microsoft/codebert-base-mlm",
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  "architectures": [
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+ "RobertaForCausalLM"
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  ],
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  "attention_probs_dropout_prob": 0.1,
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  "bos_token_id": 0,
 
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  "hidden_size": 768,
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
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+ "is_decoder": true,
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  "layer_norm_eps": 1e-05,
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  "max_position_embeddings": 514,
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  "model_type": "roberta",
 
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  "output_past": true,
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  "pad_token_id": 1,
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  "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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  "transformers_version": "4.38.2",
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  "type_vocab_size": 1,
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+ "use_cache": false,
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  "vocab_size": 50265
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  }