The model is a Portuguese language understanding model designed to generate responses to a wide range of questions and prompts. It takes as input a natural language question or prompt and outputs a corresponding response.
The model is trained on a dataset of 51k examples, which is a cleaned and translated version of the original Alpaca Dataset released by Stanford. The original dataset was translated to Portuguese (Brazil) to provide a more culturally and linguistically relevant resource for the Brazilian market.
The dataset was carefully reviewed to identify and fix issues present in the original release, ensuring that the model is trained on high-quality data. The model is intended to be used in applications where a deep understanding of Portuguese language is required, such as chatbots, virtual assistants, and language translation systems.
Intended uses:
Generating responses to natural language questions and prompts in Portuguese
Supporting chatbots, virtual assistants, and other conversational AI applications
Enhancing language translation systems and machine translation models
Providing a culturally and linguistically relevant resource for the Brazilian market
Limitations
The model may not generalize well to other languages or dialects
The model may not perform well on out-of-domain or unseen topics
The model may not be able to handle ambiguous or open-ended prompts
The model may not be able to understand nuances of regional dialects or slang
The model may not be able to handle prompts that require common sense or real-world knowledge
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
1.382
0.01
1
1.4056
1.1762
0.5
45
1.1987
1.1294
0.99
90
1.1493
1.0028
1.47
135
1.1331
0.9899
1.97
180
1.1227
Framework versions
Transformers 4.40.0.dev0
Pytorch 2.2.2+cu121
Datasets 2.15.0
Tokenizers 0.15.0
Runs of artificialguybr llama3-8b-alpacadata-ptbr on huggingface.co
26
Total runs
-9
24-hour runs
-6
3-day runs
-3
7-day runs
-15
30-day runs
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