---
library_name: transformers
license: apache-2.0
base_model: NewEden/MistralAI-Nemo-Instruct-ChatML
tags:
- axolotl
- generated_from_trainer
datasets:
- hardlyworking/HardlyRP
- jeiku/Writing
model-index:
- name: Sapphire-12B
  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`
```yaml
base_model: NewEden/MistralAI-Nemo-Instruct-ChatML
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: hardlyworking/HardlyRP
    type: chat_template
    chat_template: chatml
    roles_to_train: ["gpt"]
    field_messages: conversations
    message_field_role: from
    message_field_content: value
    train_on_eos: turn
  - path: jeiku/Writing
    type: completion
    field: text

shuffle_merged_datasets: true
dataset_prepared_path: dataset_preparedss
val_set_size: 0.0025
output_dir: 12b-out-0001-max_grad_norm

hub_model_id: hardlyworking/Sapphire-12B
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_layer_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: true

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

max_grad_norm: 0.001

wandb_project: Sapphire
wandb_entity:
wandb_watch:
wandb_name: Sapphire
wandb_log_model:

evals_per_epoch: 8
eval_table_size:
eval_max_new_tokens: 128

gradient_accumulation_steps: 8
micro_batch_size: 2
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 2e-6

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
s2_attention:

warmup_ratio: 0.05
saves_per_epoch: 1
debug:
weight_decay: 0.0001
fsdp:
fsdp_config:
special_tokens:
   pad_token: <pad>
```

</details><br>

# Sapphire-12B

This model is a fine-tuned version of [NewEden/MistralAI-Nemo-Instruct-ChatML](https://huggingface.co/NewEden/MistralAI-Nemo-Instruct-ChatML) on the hardlyworking/HardlyRP and the jeiku/Writing datasets.
It achieves the following results on the evaluation set:
- Loss: 1.6799

## 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: 2e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: 30
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8932        | 0.0033 | 1    | 1.9155          |
| 1.7729        | 0.1262 | 38   | 1.7802          |
| 1.7163        | 0.2525 | 76   | 1.7111          |
| 1.6484        | 0.3787 | 114  | 1.6970          |
| 1.7006        | 0.5050 | 152  | 1.6907          |
| 1.7276        | 0.6312 | 190  | 1.6874          |
| 1.7042        | 0.7575 | 228  | 1.6847          |
| 1.5575        | 0.8837 | 266  | 1.6825          |
| 1.5451        | 1.0100 | 304  | 1.6816          |
| 1.6592        | 1.1362 | 342  | 1.6807          |
| 1.7344        | 1.2625 | 380  | 1.6805          |
| 1.6953        | 1.3887 | 418  | 1.6798          |
| 1.5799        | 1.5150 | 456  | 1.6799          |
| 1.5241        | 1.6412 | 494  | 1.6799          |
| 1.548         | 1.7674 | 532  | 1.6797          |
| 1.6254        | 1.8937 | 570  | 1.6799          |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1