Update README.md

README.md

@@ -60,15 +60,16 @@ Also, these models were trained by leveraging [scaling laws](https://arxiv.org/a
 
 This repository has the [source code](https://github.com/Nkluge-correa/Aira) used to train this model. The main libraries used are:
 
-- Transformers
-- PyTorch
-- Datasets
-- Tokenizers
-- Accelerate codecarbon sentencepiece
+- [Transformers](https://github.com/huggingface/transformers)
+- [PyTorch](https://github.com/pytorch/pytorch)
+- [Datasets](https://github.com/huggingface/datasets)
+- [Tokenizers](https://github.com/huggingface/tokenizers)
+- [Accelerate](https://github.com/huggingface/accelerate)
+- [Codecarbon](https://github.com/mlco2/codecarbon)
 
+- ## Training Set-up
 
-
-## Training Set-up
+These are the main arguments used in the training of this model:
 
 | Arguments                     | Value                                |
 |-------------------------------|--------------------------------------|
@@ -143,9 +144,15 @@ for i, completion in enumerate(completions):
 
 ## Limitations
 
-🤥 Generative AI models, like LLMs used for text generation/conversation or GANs for image generation, can produce content that can be mistaken for truth but is, in fact, misleading or entirely false, given the model's tendency to output hallucinations. Such models can generate deceptive visuals, human-like textual content, music, or combined media that might seem genuine at first glance.
+- **Hallucinations:** This model can produce content that can be mistaken for truth but is, in fact, misleading or entirely false, i.e., hallucination.
+
+- **Biases and Toxicity:** This model inherits the social and historical stereotypes from the data used to train it. Given these biases, the model can produce toxic content, i.e., harmful, offensive, or detrimental to individuals, groups, or communities.
+
+- **Unreliable Code:** The model may produce incorrect code snippets and statements. These code generations should not be treated as suggestions or accurate solutions.
+
+- **Language Limitations:** The model is primarily designed to understand standard Portuguese (BR). Other languages might challenge its comprehension, leading to potential misinterpretations or errors in response.
 
-🤬 Machine learning systems can inherit social and historical stereotypes from the data used to train them. Given these biases, models can be prone to produce toxic content, that is, text, images, videos, or comments, that is harmful, offensive, or detrimental to individuals, groups, or communities. Also, models that automate decision-making can have biases against certain groups, affecting people based on sensitive attributes in an unjust manner.
+- **Repetition and Verbosity:** The model may get stuck on repetition loops (especially if the repetition penalty during generations is set to a meager value) or produce verbose responses unrelated to the prompt it was given.
 
 ## Evaluations
 
@@ -160,7 +167,7 @@ for i, completion in enumerate(completions):
 
 | Models                                                                              | Average | [ARC](https://arxiv.org/abs/1803.05457) | [Hellaswag](https://arxiv.org/abs/1905.07830) | [MMLU](https://arxiv.org/abs/2009.03300) | [TruthfulQA](https://arxiv.org/abs/2109.07958) |
 |-------------------------------------------------------------------------------------|---------|-----------------------------------------|-----------------------------------------------|------------------------------------------|------------------------------------------------|
-| [Teeny Tiny Llama 162m](https://huggingface.co/nicholasKluge/Teeny-tiny-llama-162m) | 31.16   | 26.15                                   | 29.29                                         | 28.11                                    | 41.12                                          |
+| [TeenyTinyLlama-162m](https://huggingface.co/nicholasKluge/TeenyTinyLlama-162m)     | 31.16   | 26.15                                   | 29.29                                         | 28.11                                    | 41.12                                          |
 | [Pythia-160m](https://huggingface.co/EleutherAI/pythia-160m-deduped)                | 31.16   | 24.06                                   | 31.39                                         | 24.86                                    | 44.34                                          |
 | [OPT-125m](https://huggingface.co/facebook/opt-125m)                                | 30.80   | 22.87                                   | 31.47                                         | 26.02                                    | 42.87                                          |
 | [Gpt2-portuguese-small](https://huggingface.co/pierreguillou/gpt2-small-portuguese) | 30.22   | 22.48                                   | 29.62                                         | 27.36                                    | 41.44                                          |
@@ -168,15 +175,26 @@ for i, completion in enumerate(completions):
 
 * Evaluations on benchmarks were performed using the [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) (by [EleutherAI](https://www.eleuther.ai/)). Thanks to [Laiviet](https://github.com/laiviet/lm-evaluation-harness) for translating some of the tasks in the LM-Evaluation-Harness.
 
+## Fine Tuning
+
+| Models                                                                              | Average | [ARC](https://arxiv.org/abs/1803.05457) | [Hellaswag](https://arxiv.org/abs/1905.07830) | [MMLU](https://arxiv.org/abs/2009.03300) | [TruthfulQA](https://arxiv.org/abs/2109.07958) |
+|-------------------------------------------------------------------------------------|---------|-----------------------------------------|-----------------------------------------------|------------------------------------------|------------------------------------------------|
+| [Teeny Tiny Llama 162m](https://huggingface.co/nicholasKluge/Teeny-tiny-llama-162m) | 31.16   | 26.15                                   | 29.29                                         | 28.11                                    | 41.12                                          |
+| [Pythia-160m](https://huggingface.co/EleutherAI/pythia-160m-deduped)                | 31.16   | 24.06                                   | 31.39                                         | 24.86                                    | 44.34                                          |
+| [OPT-125m](https://huggingface.co/facebook/opt-125m)                                | 30.80   | 22.87                                   | 31.47                                         | 26.02                                    | 42.87                                          |
+| [Gpt2-portuguese-small](https://huggingface.co/pierreguillou/gpt2-small-portuguese) | 30.22   | 22.48                                   | 29.62                                         | 27.36                                    | 41.44                                          |
+| [Gpt2-small](https://huggingface.co/gpt2)                                           | 29.97   | 21.48                                   | 31.60                                         | 25.79                                    | 40.65                                          | 
+
+
 ## Cite as 🤗
 
 ```latex
 
 @misc{nicholas22llama,
   doi = {10.5281/zenodo.6989727},
-  url = {https://huggingface.co/nicholasKluge/Teeny-tiny-llama-162m},
+  url = {https://huggingface.co/nicholasKluge/TeenyTinyLlama-162m},
   author = {Nicholas Kluge Corrêa},
-  title = {Teeny-tiny-llama},
+  title = {Teeny Tiny Llama},
   year = {2023},
   publisher = {HuggingFace},
   journal = {HuggingFace repository},
@@ -186,4 +204,4 @@ for i, completion in enumerate(completions):
 
 ## License
 
-The Teeny-tiny-llama-162m is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.
+The TeenyTinyLlama-162m is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.