---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen3-4B-Base
tags:
- axolotl
- generated_from_trainer
datasets:
- GreenerPastures/All-Your-Base-Full
model-index:
- name: Sugma4B
  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: `0.10.0.dev0`
```yaml
base_model: Qwen/Qwen3-4B-Base

load_in_8bit: false
load_in_4bit: false
strict: false

chat_template: qwen3
datasets:
  - path: GreenerPastures/All-Your-Base-Full
    type: chat_template
    split: train
    field_messages: conversations
    message_property_mappings:
      role: from
      content: value
val_set_size: 0.01
output_dir: ./outputs/out
dataset_prepared_path: last_run_prepared
shuffle_merged_datasets: true

hub_model_id: hardlyworking/Sugma4B
hub_strategy: "all_checkpoints"
push_dataset_to_hub:
hf_use_auth_token: true

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

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

wandb_project: Qwen4B
wandb_entity:
wandb_watch:
wandb_name: Qwen4B
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: 1e-5

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

gradient_checkpointing: offload
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:

deepspeed:

warmup_ratio: 0.05
saves_per_epoch: 1
debug:
weight_decay: 0.01
fsdp:
fsdp_config:
special_tokens:
   pad_token:
```

</details><br>

# Sugma4B

This model is a fine-tuned version of [Qwen/Qwen3-4B-Base](https://huggingface.co/Qwen/Qwen3-4B-Base) on the GreenerPastures/All-Your-Base-Full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9300

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 4
- 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: 52
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1154        | 0.0019 | 1    | 1.1372          |
| 0.9351        | 0.125  | 65   | 1.0074          |
| 0.8884        | 0.25   | 130  | 0.9758          |
| 0.9853        | 0.375  | 195  | 0.9608          |
| 0.8998        | 0.5    | 260  | 0.9490          |
| 0.8919        | 0.625  | 325  | 0.9420          |
| 0.914         | 0.75   | 390  | 0.9376          |
| 0.8873        | 0.875  | 455  | 0.9346          |
| 0.8854        | 1.0    | 520  | 0.9326          |
| 0.9365        | 1.125  | 585  | 0.9316          |
| 0.8865        | 1.25   | 650  | 0.9308          |
| 0.9696        | 1.375  | 715  | 0.9304          |
| 0.9119        | 1.5    | 780  | 0.9302          |
| 0.8793        | 1.625  | 845  | 0.9301          |
| 0.9265        | 1.75   | 910  | 0.9301          |
| 0.9375        | 1.875  | 975  | 0.9301          |
| 0.8473        | 2.0    | 1040 | 0.9300          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1