Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- _load_in_8bit: False
- _load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float16
- bnb_4bit_quant_storage: uint8
- load_in_4bit: True
- load_in_8bit: False
Framework versions
- PEFT 0.5.0
Open Portuguese LLM Leaderboard Evaluation Results
Detailed results can be found here and on the 🚀 Open Portuguese LLM Leaderboard
| Metric | Value |
|---|---|
| Average | 63.57 |
| ENEM Challenge (No Images) | 56.82 |
| BLUEX (No Images) | 47.15 |
| OAB Exams | 36.31 |
| Assin2 RTE | 88.92 |
| Assin2 STS | 76.37 |
| FaQuAD NLI | 67.17 |
| HateBR Binary | 82.02 |
| PT Hate Speech Binary | 69.24 |
| tweetSentBR | 48.14 |
- Downloads last month
- 2
Unable to determine this model’s pipeline type. Check the
docs
.
Space using recogna-nlp/mistralbode_7b_qlora_ultraalpaca 1
Evaluation results
- accuracy on ENEM Challenge (No Images)Open Portuguese LLM Leaderboard56.820
- accuracy on BLUEX (No Images)Open Portuguese LLM Leaderboard47.150
- accuracy on OAB ExamsOpen Portuguese LLM Leaderboard36.310
- f1-macro on Assin2 RTEtest set Open Portuguese LLM Leaderboard88.920
- pearson on Assin2 STStest set Open Portuguese LLM Leaderboard76.370
- f1-macro on FaQuAD NLItest set Open Portuguese LLM Leaderboard67.170
- f1-macro on HateBR Binarytest set Open Portuguese LLM Leaderboard82.020
- f1-macro on PT Hate Speech Binarytest set Open Portuguese LLM Leaderboard69.240
- f1-macro on tweetSentBRtest set Open Portuguese LLM Leaderboard48.140