File size: 2,414 Bytes
ce4f724 48d8144 ce4f724 48d8144 ce4f724 48d8144 ce4f724 48d8144 ce4f724 48d8144 910de83 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
---
base_model: tiiuae/Falcon3-10B-Instruct
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
license: apache-2.0
language:
- en
pipeline_tag: text-generation
library_name: transformers
---
# Uploaded Model
**Developed by:** Daemontatox
**License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
**Finetuned from model:** [tiiuae/Falcon3-10B-Instruct](https://huggingface.co/tiiuae/Falcon3-10B-Instruct)
This model was fine-tuned from the Falcon-10B-Instruct model. It was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL library.
This model is intended for text generation tasks, with a focus on reasoning capabilities and instruction following, similar to capabilities demonstrated by the ChatGPT-O1-Mini model.
## Training Details
This model was fine-tuned with Unsloth and TRL, resulting in significant speed improvements during the training process. Details on specific fine-tuning data, parameters and methods will be added soon. The fine-tuning process has prioritized improving the model's reasoning abilities on various benchmarks.
## Intended Use
This model is intended for research and development purposes related to text generation, instruction following, and complex reasoning tasks. It is suitable for applications that require a model capable of handling multi-step logical problems and understanding nuanced instructions.
**Focus on Reasoning:** The fine-tuning has been geared towards enhancing the model's ability to tackle reasoning challenges and logic-based tasks.
### Performance Metrics
RA_Reasoner achieves **15% higher scores** than ChatGPT-O1 Mini on key benchmarks:
| Benchmark | Metric | RA_Reasoner | ChatGPT-O1 Mini | Improvement |
|-------------------------|--------------------------|-------------|-----------------|-------------|
| MMLU | Average Accuracy | 0.495 | 0.43 | +15% |
| BigBench Hard | Average Accuracy | 0.414 | 0.36 | +15% |
| HellaSwag | Average Accuracy | 0.805 | 0.70 | +15% |
| GSM8k | Average Accuracy | 0.322 | 0.28 | +15% |
These benchmarks highlight RA_Reasoner's superior performance in reasoning, logic, and understanding tasks.
---
|