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- library_name: transformers
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- tags: []
 
 
 
 
 
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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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- <!-- Provide a longer summary of what this model is. -->
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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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- - **Developed by:** [More Information Needed]
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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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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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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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- [More Information Needed]
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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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- ## 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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- ## Glossary [optional]
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- ## More Information [optional]
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  ---
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+ license: apache-2.0
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+ base_model: distilbert/distilgpt2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: tiny-gpt2-br
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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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+ # tiny-gpt2-br
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+ This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 4.3565
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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: 8e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 3
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 6.6049 | 0.21 | 1000 | 5.6029 |
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+ | 5.4429 | 0.42 | 2000 | 5.1985 |
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+ | 5.1379 | 0.63 | 3000 | 4.9480 |
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+ | 4.9697 | 0.84 | 4000 | 4.8117 |
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+ | 4.82 | 1.05 | 5000 | 4.7015 |
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+ | 4.7219 | 1.26 | 6000 | 4.6272 |
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+ | 4.648 | 1.47 | 7000 | 4.5548 |
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+ | 4.6005 | 1.68 | 8000 | 4.5024 |
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+ | 4.5511 | 1.89 | 9000 | 4.4625 |
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+ | 4.4843 | 2.1 | 10000 | 4.4290 |
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+ | 4.4343 | 2.31 | 11000 | 4.4026 |
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+ | 4.4215 | 2.52 | 12000 | 4.3810 |
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+ | 4.4033 | 2.73 | 13000 | 4.3652 |
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+ | 4.3886 | 2.94 | 14000 | 4.3565 |
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+ ### Framework versions
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+ - Transformers 4.39.1
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 50256,
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+ "eos_token_id": 50256,
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+ "transformers_version": "4.39.1"
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+ }
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