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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: ctrltokyo/llm_prompt_mask_fill_model |
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results: [] |
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datasets: |
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- sahil2801/code_instructions_120k |
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metrics: |
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- accuracy |
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language: |
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- en |
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widget: |
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- text: "A web application with a REST API on Rails. This will be used for [MASK]." |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# ctrltokyo/llm_prompt_mask_fill_model |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [code_instructions_120k](https://huggingface.co/datasets/sahil2801/code_instructions_120k) dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 2.1215 |
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- Validation Loss: 1.5672 |
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- Epoch: 0 |
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## Model description |
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It's just distilbert-base-uncased with some fine tuning. |
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## Intended uses & limitations |
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This model could be used for live autocompletion of PROMPTS in a coding-specific chatbot. Don't try this on code, because it won't work. |
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## Training and evaluation data |
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Evaluated on 5% of training data. No further evaluation performed at this point. Trained on NVIDIA V100. |
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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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- optimizer: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 108, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000} |
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- training_precision: mixed_float16 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 2.1215 | 1.5672 | 0 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.14.1 |
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- Tokenizers 0.13.3 |
