metadata
license: apache-2.0
tags:
- generated_from_trainer
- axolotl
base_model: mistralai/Mistral-Nemo-Base-2407
datasets:
- cognitivecomputations/Dolphin-2.9
- teknium/OpenHermes-2.5
- m-a-p/CodeFeedback-Filtered-Instruction
- cognitivecomputations/dolphin-coder
- cognitivecomputations/samantha-data
- microsoft/orca-math-word-problems-200k
- Locutusque/function-calling-chatml
- internlm/Agent-FLAN
model-index:
- name: dolphin-2.9.3-mistral-nemo-12b
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: ENEM Challenge (No Images)
type: eduagarcia/enem_challenge
split: train
args:
num_few_shot: 3
metrics:
- type: acc
value: 72.08
name: accuracy
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BLUEX (No Images)
type: eduagarcia-temp/BLUEX_without_images
split: train
args:
num_few_shot: 3
metrics:
- type: acc
value: 62.45
name: accuracy
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: OAB Exams
type: eduagarcia/oab_exams
split: train
args:
num_few_shot: 3
metrics:
- type: acc
value: 52.71
name: accuracy
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Assin2 RTE
type: assin2
split: test
args:
num_few_shot: 15
metrics:
- type: f1_macro
value: 93.08
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Assin2 STS
type: eduagarcia/portuguese_benchmark
split: test
args:
num_few_shot: 15
metrics:
- type: pearson
value: 80.83
name: pearson
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: FaQuAD NLI
type: ruanchaves/faquad-nli
split: test
args:
num_few_shot: 15
metrics:
- type: f1_macro
value: 81.28
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HateBR Binary
type: ruanchaves/hatebr
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 85.85
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: PT Hate Speech Binary
type: hate_speech_portuguese
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 73.07
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: tweetSentBR
type: eduagarcia/tweetsentbr_fewshot
split: test
args:
num_few_shot: 25
metrics:
- type: f1_macro
value: 72.36
name: f1-macro
source:
url: >-
https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
name: Open Portuguese LLM Leaderboard
Dolphin 2.9.3 Mistral Nemo 12b 🐬
Curated and trained by Eric Hartford and Cognitive Computations
Our appreciation for the sponsors of Dolphin 2.9.3:
- Crusoe Cloud - provided excellent on-demand 8xL40S node
This model is based on mistralai/Mistral-Nemo-Base-2407, and is governed by the apache 2.0 license.
The base model has 128K context, and our finetuning used 8192 sequence length.
Dolphin 2.9.3 uses ChatML prompt template format.
example:
<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Dolphin-2.9.3 has a variety of instruction following, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
Dolphin is licensed according to apache 2.0 license. We grant permission for any use, including commercial. Dolphin was trained on data generated from GPT4, among other models.
Evals
See evals
| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr|
|-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|leaderboard |N/A |none | 0|acc |↑ |0.3437|± |0.0043|
| | |none | 0|acc_norm |↑ |0.5076|± |0.0053|
| | |none | 0|exact_match |↑ |0.0536|± |0.0061|
| | |none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A |
| | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A |
| | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199|
| | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186|
| - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.5549|± |0.0061|
| - leaderboard_bbh_boolean_expressions | 0|none | 3|acc_norm |↑ |0.8640|± |0.0217|
| - leaderboard_bbh_causal_judgement | 0|none | 3|acc_norm |↑ |0.6417|± |0.0352|
| - leaderboard_bbh_date_understanding | 0|none | 3|acc_norm |↑ |0.6080|± |0.0309|
| - leaderboard_bbh_disambiguation_qa | 0|none | 3|acc_norm |↑ |0.6480|± |0.0303|
| - leaderboard_bbh_formal_fallacies | 0|none | 3|acc_norm |↑ |0.5360|± |0.0316|
| - leaderboard_bbh_geometric_shapes | 0|none | 3|acc_norm |↑ |0.5240|± |0.0316|
| - leaderboard_bbh_hyperbaton | 0|none | 3|acc_norm |↑ |0.6440|± |0.0303|
| - leaderboard_bbh_logical_deduction_five_objects | 0|none | 3|acc_norm |↑ |0.4600|± |0.0316|
| - leaderboard_bbh_logical_deduction_seven_objects | 0|none | 3|acc_norm |↑ |0.4680|± |0.0316|
| - leaderboard_bbh_logical_deduction_three_objects | 0|none | 3|acc_norm |↑ |0.7000|± |0.0290|
| - leaderboard_bbh_movie_recommendation | 0|none | 3|acc_norm |↑ |0.8160|± |0.0246|
| - leaderboard_bbh_navigate | 0|none | 3|acc_norm |↑ |0.6040|± |0.0310|
| - leaderboard_bbh_object_counting | 0|none | 3|acc_norm |↑ |0.3680|± |0.0306|
| - leaderboard_bbh_penguins_in_a_table | 0|none | 3|acc_norm |↑ |0.5548|± |0.0413|
| - leaderboard_bbh_reasoning_about_colored_objects | 0|none | 3|acc_norm |↑ |0.6320|± |0.0306|
| - leaderboard_bbh_ruin_names | 0|none | 3|acc_norm |↑ |0.7440|± |0.0277|
| - leaderboard_bbh_salient_translation_error_detection | 0|none | 3|acc_norm |↑ |0.5280|± |0.0316|
| - leaderboard_bbh_snarks | 0|none | 3|acc_norm |↑ |0.6292|± |0.0363|
| - leaderboard_bbh_sports_understanding | 0|none | 3|acc_norm |↑ |0.8040|± |0.0252|
| - leaderboard_bbh_temporal_sequences | 0|none | 3|acc_norm |↑ |0.4680|± |0.0316|
| - leaderboard_bbh_tracking_shuffled_objects_five_objects | 0|none | 3|acc_norm |↑ |0.2160|± |0.0261|
| - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 0|none | 3|acc_norm |↑ |0.1160|± |0.0203|
| - leaderboard_bbh_tracking_shuffled_objects_three_objects| 0|none | 3|acc_norm |↑ |0.3000|± |0.0290|
| - leaderboard_bbh_web_of_lies | 0|none | 3|acc_norm |↑ |0.4880|± |0.0317|
| - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.3146|± |0.0135|
| - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.3182|± |0.0332|
| - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.3187|± |0.0200|
| - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.3080|± |0.0218|
| - leaderboard_ifeval | 2|none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A |
| | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A |
| | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199|
| | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186|
| - leaderboard_math_algebra_hard | 1|none | 4|exact_match |↑ |0.0749|± |0.0150|
| - leaderboard_math_counting_and_prob_hard | 1|none | 4|exact_match |↑ |0.0244|± |0.0140|
| - leaderboard_math_geometry_hard | 1|none | 4|exact_match |↑ |0.0227|± |0.0130|
| - leaderboard_math_hard |N/A |none | 4|exact_match |↑ |0.0536|± |0.0061|
| - leaderboard_math_intermediate_algebra_hard | 1|none | 4|exact_match |↑ |0.0250|± |0.0093|
| - leaderboard_math_num_theory_hard | 1|none | 4|exact_match |↑ |0.0390|± |0.0156|
| - leaderboard_math_prealgebra_hard | 1|none | 4|exact_match |↑ |0.1295|± |0.0242|
| - leaderboard_math_precalculus_hard | 1|none | 4|exact_match |↑ |0.0296|± |0.0146|
| - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.3437|± |0.0043|
| - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.4511|± |0.0178|
| - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.5880|± |0.0312|
| - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.3438|± |0.0297|
| - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.4240|± |0.0313|
| Groups |Version|Filter|n-shot| Metric | |Value | |Stderr|
|------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
|leaderboard |N/A |none | 0|acc |↑ |0.3437|± |0.0043|
| | |none | 0|acc_norm |↑ |0.5076|± |0.0053|
| | |none | 0|exact_match |↑ |0.0536|± |0.0061|
| | |none | 0|inst_level_loose_acc |↑ |0.4388|± |N/A |
| | |none | 0|inst_level_strict_acc |↑ |0.3741|± |N/A |
| | |none | 0|prompt_level_loose_acc |↑ |0.3105|± |0.0199|
| | |none | 0|prompt_level_strict_acc|↑ |0.2477|± |0.0186|
| - leaderboard_bbh |N/A |none | 3|acc_norm |↑ |0.5549|± |0.0061|
| - leaderboard_gpqa |N/A |none | 0|acc_norm |↑ |0.3146|± |0.0135|
| - leaderboard_math_hard|N/A |none | 4|exact_match |↑ |0.0536|± |0.0061|
| - leaderboard_musr |N/A |none | 0|acc_norm |↑ |0.4511|± |0.0178|
Training
See axolotl config
axolotl version: 0.4.1
base_model: /workspace/models/Mistral-Nemo-Base-2407
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
# load_in_4bit: true
strict: false
datasets:
- path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl
type: sharegpt
conversation: chatml
chat_template: chatml
# adapter: qlora
# lora_r: 128
# lora_alpha: 16
# lora_modules_to_save: [embed_tokens, lm_head]
# lora_dropout: 0.05
# lora_target_linear: true
unfrozen_parameters:
- ^lm_head.weight$
- ^model.embed_tokens.weight$
- input_layernorm
- model.norm
- post_attention_layernorm
- self_attn.rotary_emb
# mlp.down_proj layers
- model.layers.0.mlp.down_proj
- model.layers.1.mlp.down_proj
- model.layers.4.mlp.down_proj
- model.layers.37.mlp.down_proj
- model.layers.24.mlp.down_proj
- model.layers.2.mlp.down_proj
- model.layers.38.mlp.down_proj
- model.layers.35.mlp.down_proj
- model.layers.25.mlp.down_proj
- model.layers.6.mlp.down_proj
- model.layers.22.mlp.down_proj
- model.layers.23.mlp.down_proj
- model.layers.3.mlp.down_proj
- model.layers.21.mlp.down_proj
- model.layers.5.mlp.down_proj
- model.layers.28.mlp.down_proj
- model.layers.20.mlp.down_proj
- model.layers.26.mlp.down_proj
- model.layers.19.mlp.down_proj
- model.layers.34.mlp.down_proj
# mlp.gate_proj layers
- model.layers.2.mlp.gate_proj
- model.layers.1.mlp.gate_proj
- model.layers.3.mlp.gate_proj
- model.layers.5.mlp.gate_proj
- model.layers.4.mlp.gate_proj
- model.layers.35.mlp.gate_proj
- model.layers.36.mlp.gate_proj
- model.layers.37.mlp.gate_proj
- model.layers.38.mlp.gate_proj
- model.layers.34.mlp.gate_proj
- model.layers.33.mlp.gate_proj
- model.layers.8.mlp.gate_proj
- model.layers.32.mlp.gate_proj
- model.layers.6.mlp.gate_proj
- model.layers.28.mlp.gate_proj
- model.layers.26.mlp.gate_proj
- model.layers.30.mlp.gate_proj
- model.layers.23.mlp.gate_proj
- model.layers.29.mlp.gate_proj
- model.layers.27.mlp.gate_proj
# mlp.up_proj layers
- model.layers.3.mlp.up_proj
- model.layers.4.mlp.up_proj
- model.layers.6.mlp.up_proj
- model.layers.2.mlp.up_proj
- model.layers.5.mlp.up_proj
- model.layers.8.mlp.up_proj
- model.layers.10.mlp.up_proj
- model.layers.9.mlp.up_proj
- model.layers.7.mlp.up_proj
- model.layers.0.mlp.up_proj
- model.layers.17.mlp.up_proj
- model.layers.15.mlp.up_proj
- model.layers.22.mlp.up_proj
- model.layers.18.mlp.up_proj
- model.layers.16.mlp.up_proj
- model.layers.11.mlp.up_proj
- model.layers.21.mlp.up_proj
- model.layers.23.mlp.up_proj
- model.layers.20.mlp.up_proj
- model.layers.27.mlp.up_proj
# self_attn.k_proj layers
- model.layers.30.self_attn.k_proj
- model.layers.27.self_attn.k_proj
- model.layers.25.self_attn.k_proj
- model.layers.33.self_attn.k_proj
- model.layers.26.self_attn.k_proj
- model.layers.31.self_attn.k_proj
- model.layers.35.self_attn.k_proj
- model.layers.39.self_attn.k_proj
- model.layers.22.self_attn.k_proj
- model.layers.24.self_attn.k_proj
- model.layers.21.self_attn.k_proj
- model.layers.28.self_attn.k_proj
- model.layers.23.self_attn.k_proj
- model.layers.36.self_attn.k_proj
- model.layers.20.self_attn.k_proj
- model.layers.37.self_attn.k_proj
- model.layers.29.self_attn.k_proj
- model.layers.32.self_attn.k_proj
- model.layers.16.self_attn.k_proj
- model.layers.18.self_attn.k_proj
# self_attn.o_proj layers
- model.layers.7.self_attn.o_proj
- model.layers.6.self_attn.o_proj
- model.layers.9.self_attn.o_proj
- model.layers.5.self_attn.o_proj
- model.layers.27.self_attn.o_proj
- model.layers.26.self_attn.o_proj
- model.layers.4.self_attn.o_proj
- model.layers.31.self_attn.o_proj
- model.layers.8.self_attn.o_proj
- model.layers.16.self_attn.o_proj
- model.layers.3.self_attn.o_proj
- model.layers.10.self_attn.o_proj
- model.layers.18.self_attn.o_proj
- model.layers.33.self_attn.o_proj
- model.layers.17.self_attn.o_proj
- model.layers.32.self_attn.o_proj
- model.layers.30.self_attn.o_proj
- model.layers.2.self_attn.o_proj
- model.layers.15.self_attn.o_proj
- model.layers.11.self_attn.o_proj
# self_attn.q_proj layers
- model.layers.14.self_attn.q_proj
- model.layers.11.self_attn.q_proj
- model.layers.15.self_attn.q_proj
- model.layers.9.self_attn.q_proj
- model.layers.8.self_attn.q_proj
- model.layers.18.self_attn.q_proj
- model.layers.12.self_attn.q_proj
- model.layers.13.self_attn.q_proj
- model.layers.19.self_attn.q_proj
- model.layers.16.self_attn.q_proj
- model.layers.10.self_attn.q_proj
- model.layers.17.self_attn.q_proj
- model.layers.7.self_attn.q_proj
- model.layers.5.self_attn.q_proj
- model.layers.20.self_attn.q_proj
- model.layers.3.self_attn.q_proj
- model.layers.26.self_attn.q_proj
- model.layers.27.self_attn.q_proj
- model.layers.28.self_attn.q_proj
- model.layers.33.self_attn.q_proj
# self_attn.v_proj layers
- model.layers.27.self_attn.v_proj
- model.layers.20.self_attn.v_proj
- model.layers.24.self_attn.v_proj
- model.layers.25.self_attn.v_proj
- model.layers.30.self_attn.v_proj
- model.layers.2.self_attn.v_proj
- model.layers.23.self_attn.v_proj
- model.layers.22.self_attn.v_proj
- model.layers.26.self_attn.v_proj
- model.layers.33.self_attn.v_proj
- model.layers.37.self_attn.v_proj
- model.layers.7.self_attn.v_proj
- model.layers.4.self_attn.v_proj
- model.layers.18.self_attn.v_proj
- model.layers.31.self_attn.v_proj
- model.layers.17.self_attn.v_proj
- model.layers.35.self_attn.v_proj
- model.layers.32.self_attn.v_proj
- model.layers.21.self_attn.v_proj
- model.layers.3.self_attn.v_proj
dataset_prepared_path: /workspace/axolotl/dolph-2.9.3-nemo-prepared
val_set_size: 0.01
output_dir: /workspace/axolotl/dolphin-2.9.3-mistral-nemo
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
wandb_project: dolphin-2.9.3-Mistral-nemo
wandb_watch:
wandb_run_id:
wandb_log_model:
gradient_accumulation_steps: 16
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 5e-6
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32:
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 100
# evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 1
save_total_limit: 2
save_steps:
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.1
special_tokens:
eos_token: "<|im_end|>"
pad_token: "<pad>"
bos_token: "<s>"
unk_token: "<unk>"
tokens:
- "<|im_start|>"
# fsdp:
# - full_shard
# - auto_wrap
# fsdp_config:
# fsdp_limit_all_gathers: true
# fsdp_sync_module_states: true
# fsdp_offload_params: true
# fsdp_use_orig_params: false
# fsdp_cpu_ram_efficient_loading: true
# fsdp_transformer_layer_cls_to_wrap: MixtralSparseMoeBlock
# fsdp_state_dict_type: FULL_STATE_DICT
# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
# fsdp_sharding_strategy: FULL_SHARD
# fsdp_forward_prefetch: false
# fsdp_backward_prefetch: BACKWARD_PRE
workspace/axolotl/dolphin-2.9.3-mistral-nemo
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5605
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5691 | 1.0162 | 983 | 0.5734 |
| 0.5335 | 2.0174 | 1968 | 0.5609 |
| 0.5297 | 2.9639 | 2901 | 0.5605 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
Open Portuguese LLM Leaderboard Evaluation Results
Detailed results can be found here and on the 🚀 Open Portuguese LLM Leaderboard
| Metric | Value |
|---|---|
| Average | 74.86 |
| ENEM Challenge (No Images) | 72.08 |
| BLUEX (No Images) | 62.45 |
| OAB Exams | 52.71 |
| Assin2 RTE | 93.08 |
| Assin2 STS | 80.83 |
| FaQuAD NLI | 81.28 |
| HateBR Binary | 85.85 |
| PT Hate Speech Binary | 73.07 |
| tweetSentBR | 72.36 |