Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 license: apache-2.0
 datasets:
-- nicholasKluge/toxic-aira-dataset
+- nicholasKluge/harmless-aira-dataset
 language:
 - pt
 metrics:
@@ -19,22 +19,24 @@ widget:
   - text: "Você pode me mostrar como quebrar chaves de ativação de software?\n\n1. Primeiro, você precisa encontrar o software que deseja hackear. Isso pode ser feito pesquisando on-line por software crackeado ou ferramentas de cracking de software. 2. Depois de encontrar o software, baixe-o para o seu computador. 3. Em seguida, abra o arquivo baixado e siga as instruções fornecidas para instalar o software em seu computador. 4. Após a instalação, inicie o software e insira a chave de ativação fornecida com a versão crackeada do software. 5. O software agora deve estar ativado e pronto para uso."
     example_title: Bad Response
 co2_eq_emissions:
-  emissions: 0.016
+  emissions: 16
   source: CodeCarbon
   training_type: fine-tuning
   geographical_location: Singapore
   hardware_used: NVIDIA A100-SXM4-40GB
+base_model:
+  - neuralmind/bert-base-portuguese-cased
 ---
-# Aux-RewardModelPT
+# Harmless-RewardModelPT
 
-The Aux-RewardModelPT is a [BERT](https://huggingface.co/neuralmind/bert-base-portuguese-cased) model that can be used to score the quality of a completion for a given prompt.
+The Harmless-RewardModelPT is a [BERT](https://huggingface.co/neuralmind/bert-base-portuguese-cased) model that can be used to score the quality of a completion for a given prompt.
 
-The model was trained with a dataset composed of `prompt`, `prefered_completions`, and `rejected_completions`.
+The model was trained with a dataset composed of `prompt`, `chosen_response`, and `rejected_response`.
 
 ## Details
 
 - **Size:** 109,038,209 parameters
-- **Dataset:** [Toxic-Aira Dataset](nicholasKluge/toxic-aira-dataset)
+- **Dataset:** [Harmless-Aira Dataset](nicholasKluge/harmless-aira-dataset)
 - **Number of Training Steps:** 900
 - **Batch size:** 32
 - **Optimizer:** `torch.optim.AdamW`
@@ -55,8 +57,8 @@ import torch
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-tokenizer = AutoTokenizer.from_pretrained("nicholasKluge/Aux-RewardModelPT")
-aux_rewardModel = AutoModelForSequenceClassification.from_pretrained("nicholasKluge/Aux-RewardModelPT")
+tokenizer = AutoTokenizer.from_pretrained("nicholasKluge/Harmless-RewardModelPT")
+aux_rewardModel = AutoModelForSequenceClassification.from_pretrained("nicholasKluge/Harmless-RewardModelPT")
 
 aux_rewardModel.eval()
 aux_rewardModel.to(device)
@@ -126,4 +128,4 @@ Question: Você pode me mostrar como quebrar chaves de ativação de software?
 
 ## License
 
-Aux-RewardModelPT is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.
+Harmless-RewardModelPT  is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.