AiAF / Pretraining-SCPWiki-032025-12B-Instruct

huggingface.co
Total runs: 19
24-hour runs: 0
7-day runs: 4
30-day runs: 9
Model's Last Updated: March 09 2025
text-generation

Introduction of Pretraining-SCPWiki-032025-12B-Instruct

Model Details of Pretraining-SCPWiki-032025-12B-Instruct

Built with Axolotl

See axolotl config

axolotl version: 0.8.0.dev0

base_model: mistralai/Mistral-Nemo-Base-2407
# optionally might have model_type or tokenizer_type
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
# Automatically upload checkpoint and final model to HF
hub_model_id: AiAF/Pretraining-SCPWiki-032025-12B-Instruct

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: AiAF/Pretraining-SCPWiki-032025-7B-Instruct-pretraining.jsonl
    type: completion
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./outputs/out/Pretraining-SCPWiki-032025-12B-V1

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false

wandb_project: "LLM-Pretraining"
wandb_entity:
wandb_watch: "all"
wandb_name: "Pretraining-SCPWiki-032025-12B-V1"
wandb_log_model: "false"

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000005

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3

save_total_limit: 30
warmup_steps: 10
evals_per_epoch: 20
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 20
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
  pad_token: "<pad>"
  bos_token: "<s>"
  unk_token: "<unk>"
tokens:
  - "<|im_start|>"


Pretraining-SCPWiki-032025-12B-Instruct

This model is a fine-tuned version of mistralai/Mistral-Nemo-Base-2407 on the AiAF/Pretraining-SCPWiki-032025-7B-Instruct-pretraining.jsonl dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5467
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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 1.0
Training results
Training Loss Epoch Step Validation Loss
3.1576 0.0018 1 3.5143
1.4459 0.0511 29 1.6213
1.4502 0.1022 58 1.6003
1.5545 0.1534 87 1.5870
1.3624 0.2045 116 1.5779
1.3053 0.2556 145 1.5691
1.5688 0.3067 174 1.5635
1.7144 0.3579 203 1.5594
1.5199 0.4090 232 1.5550
1.2483 0.4601 261 1.5516
1.4053 0.5112 290 1.5493
1.4238 0.5624 319 1.5486
1.4939 0.6135 348 1.5477
1.4072 0.6646 377 1.5472
1.6039 0.7157 406 1.5469
1.3127 0.7669 435 1.5468
1.4754 0.8180 464 1.5466
1.5992 0.8691 493 1.5467
1.421 0.9202 522 1.5467
1.2666 0.9714 551 1.5467
Framework versions
  • Transformers 4.49.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Runs of AiAF Pretraining-SCPWiki-032025-12B-Instruct on huggingface.co

19
Total runs
0
24-hour runs
7
3-day runs
4
7-day runs
9
30-day runs

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