---
library_name: transformers
license: mit
base_model: unsloth/phi-4
tags:
- generated_from_trainer
datasets:
- shisa-ai/shisa-v2-best-of-n-athenev2-tulu70b-llama33-only-no-sysprompt
- shisa-ai/shisa-v2-roleplaying-sft
- shisa-ai/translation_expanded_master_set_filtered
- shisa-ai/rewild-set
- shisa-ai/magpie-ultra-set
- shisa-ai/magpie-advanced-questions-set
- shisa-ai/japan-magpie-set
model-index:
- name: outputs/ablation-114-bestofn.atlo.rp.tlx.newmix2.unphi-shisa-v2-unphi-4-14b
  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. -->

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<details><summary>See axolotl config</summary>

axolotl version: `0.8.0.dev0`
```yaml
base_model: unsloth/phi-4
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

# User Liger
plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: true

chat_template: tokenizer_default
datasets:
  - path: shisa-ai/shisa-v2-best-of-n-athenev2-tulu70b-llama33-only-no-sysprompt
    type: chat_template
    field_messages: conversations
    message_field_role: from
    message_field_content: value
  - path: shisa-ai/shisa-v2-roleplaying-sft
    type: chat_template
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      system:
        - system
      assistant:
        - gpt
        - model
        - assistant
      user:
        - human
        - user
    roles_to_train: ["assistant"]
  - path: shisa-ai/translation_expanded_master_set_filtered
    split: train[:25%]
    type: chat_template
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      system:
        - system
      assistant:
        - gpt
        - model
        - assistant
      user:
        - human
        - user
    roles_to_train: ["assistant"]
  - path: shisa-ai/rewild-set
    split: train[:5%]
    type: chat_template
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      system:
        - system
      assistant:
        - gpt
        - model
        - assistant
      user:
        - human
        - user
    roles_to_train: ["assistant"]
  - path: shisa-ai/magpie-ultra-set
    split: train[:8%]
    type: chat_template
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      system:
        - system
      assistant:
        - gpt
        - model
        - assistant
      user:
        - human
        - user
    roles_to_train: ["assistant"]
  - path: shisa-ai/magpie-advanced-questions-set
    split: train[:8%]
    type: chat_template
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      system:
        - system
      assistant:
        - gpt
        - model
        - assistant
      user:
        - human
        - user
    roles_to_train: ["assistant"]
  - path: shisa-ai/japan-magpie-set
    split: train
    type: chat_template
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      system:
        - system
      assistant:
        - gpt
        - model
        - assistant
      user:
        - human
        - user
    roles_to_train: ["assistant"]

dataset_prepared_path: last_run_prepared
val_set_size: 0.05
output_dir: ./outputs/ablation-114-bestofn.atlo.rp.tlx.newmix2.unphi-shisa-v2-unphi-4-14b

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true

# marginal difference
neftune_noise_alpha: 5

use_wandb: true
wandb_project: shisa-v2
wandb_entity: augmxnt
wandb_name: ablation-114-bestofn.atlo.rp.tlx.newmix2.unphi-shisa-v2-unphi-4-14b

gradient_accumulation_steps: 1
micro_batch_size: 4
num_epochs: 3
optimizer: paged_adamw_8bit
lr_scheduler: linear
learning_rate: 5e-6

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

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_ratio: 0.1
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 0
save_total_limit: 1 # Only store a single checkpoint
debug:
deepspeed: zero3_bf16.json
weight_decay: 0.0001
fsdp:
fsdp_config:
special_tokens:
  # pad_token: "<|dummy_87|>"

```

</details><br>

# outputs/ablation-114-bestofn.atlo.rp.tlx.newmix2.unphi-shisa-v2-unphi-4-14b

This model is a fine-tuned version of [unsloth/phi-4](https://huggingface.co/unsloth/phi-4) on the shisa-ai/shisa-v2-best-of-n-athenev2-tulu70b-llama33-only-no-sysprompt, the shisa-ai/shisa-v2-roleplaying-sft, the shisa-ai/translation_expanded_master_set_filtered, the shisa-ai/rewild-set, the shisa-ai/magpie-ultra-set, the shisa-ai/magpie-advanced-questions-set and the shisa-ai/japan-magpie-set datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4720

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 296
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7211        | 0.0010 | 1    | 0.7194          |
| 0.542         | 0.2508 | 248  | 0.5293          |
| 0.4985        | 0.5015 | 496  | 0.5020          |
| 0.4755        | 0.7523 | 744  | 0.4898          |
| 0.4368        | 1.0030 | 992  | 0.4833          |
| 0.4605        | 1.2538 | 1240 | 0.4796          |
| 0.4388        | 1.5046 | 1488 | 0.4758          |
| 0.4494        | 1.7553 | 1736 | 0.4723          |
| 0.3682        | 2.0061 | 1984 | 0.4753          |
| 0.4104        | 2.2568 | 2232 | 0.4742          |
| 0.3903        | 2.5076 | 2480 | 0.4732          |
| 0.3818        | 2.7583 | 2728 | 0.4720          |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1
