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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: ctrltokyo/llm_prompt_mask_fill_model
results: []
datasets:
- sahil2801/code_instructions_120k
metrics:
- accuracy
language:
- en
widget:
- text: "A web application with a REST API on Rails. This will be used for [MASK]."
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# ctrltokyo/llm_prompt_mask_fill_model
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.
It achieves the following results on the evaluation set:
- Train Loss: 2.1215
- Validation Loss: 1.5672
- Epoch: 0
## Model description
It's just distilbert-base-uncased with some fine tuning.
## Intended uses & limitations
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.
## Training and evaluation data
Evaluated on 5% of training data. No further evaluation performed at this point. Trained on NVIDIA V100.
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- 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}
- training_precision: mixed_float16
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.1215 | 1.5672 | 0 |
### Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.1
- Tokenizers 0.13.3 |