---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-Nemo-Base-2407
tags:
- axolotl
- generated_from_trainer
datasets:
- AiAF/Pretraining-SCPWiki-032025-7B-Instruct-pretraining.jsonl
model-index:
- name: Pretraining-SCPWiki-032025-12B-Instruct
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.8.0.dev0`
```yaml
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|>"


```

</details><br>

# Pretraining-SCPWiki-032025-12B-Instruct

This model is a fine-tuned version of [mistralai/Mistral-Nemo-Base-2407](https://huggingface.co/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