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Model: laion/CoderForge-Preview-v3-316-axolotl__Qwen3-8B
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---
library_name: transformers
base_model: Qwen/Qwen3-8B
tags:
- generated_from_trainer
datasets:
- laion/CoderForge-Preview-v3-316
model-index:
- name: e/data1/datasets/playground/ot-baf/checkpoints/cf-v3-316-axolotl__Qwen3-8B
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: `0.16.0.dev0`
```yaml
# CoderForge v3 axolotl config template.
# Consumes the pre-tokenized laion/CoderForge-Preview-v3-<SIZE> datasets.
# Axolotl auto-detects pre-tokenized via input_ids + attention_mask + labels
# (_is_dataset_already_tokenized) and skips chat_template rendering entirely.
# Fill 316 via sed-substitution.
base_model: Qwen/Qwen3-8B
deepspeed: /e/scratch/jureap59/feuer1/code/axolotl/deepspeed_configs/zero3_bf16.json
load_in_8bit: false
load_in_4bit: false
# plugins disabled 2026-04-22: CCE + bf16 + flash-attn on aarch64/torch2.9 caused
# gradient explosion (grad_norm 9.8e+11) and loss -> 0 within first 3-7 steps.
# plugins:
# - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
# chat_template still set so tokenizer can be loaded, even though axolotl
# bypasses template rendering for pre-tokenized data.
chat_template: chatml
datasets:
- path: laion/CoderForge-Preview-v3-316
# No `type:` specified — axolotl's _is_dataset_already_tokenized() fires
# early and returns the dataset as-is.
ds_type: parquet
dataset_prepared_path: /e/data1/datasets/playground/ot-baf/axolotl_dataset_cache/cf-v3-316
output_dir: /e/data1/datasets/playground/ot-baf/checkpoints/cf-v3-316-axolotl__Qwen3-8B
# hub_model_id: laion/CoderForge-Preview-v3-316-axolotl__Qwen3-8B
# hub_strategy: end
# Upstream pre-tokenized sequences can exceed 80k tokens; matches Sera v3 truncation.
sequence_len: 32768
wandb_project:
wandb_entity:
wandb_watch:
wandb_name: cf-v3-316-axolotl__Qwen3-8B
wandb_log_model:
# Matches upstream SERA config's optimization hparams for apples-to-apples.
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 1e-5
adam_beta1: 0.9
adam_beta2: 0.95
bf16: auto
tf32: false
gradient_checkpointing: true
activation_offloading: true
resume_from_checkpoint:
logging_steps: 1
flash_attention: true
loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3
warmup_ratio: 0.1875
evals_per_epoch: 0
save_strategy: epoch
weight_decay: 0.01
max_grad_norm: 1.0
special_tokens:
```
</details><br>
# e/data1/datasets/playground/ot-baf/checkpoints/cf-v3-316-axolotl__Qwen3-8B
This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the laion/CoderForge-Preview-v3-316 dataset.
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2
- training_steps: 9
### Training results
### Framework versions
- Transformers 5.5.0
- Pytorch 2.9.1+cu130
- Datasets 4.5.0
- Tokenizers 0.22.2

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{
"architectures": [
"Qwen3ForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": null,
"dtype": "bfloat16",
"eos_token_id": 151645,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 12288,
"layer_types": [
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"max_position_embeddings": 40960,
"max_window_layers": 36,
"model_type": "qwen3",
"num_attention_heads": 32,
"num_hidden_layers": 36,
"num_key_value_heads": 8,
"pad_token_id": 151643,
"rms_norm_eps": 1e-06,
"rope_parameters": {
"rope_theta": 1000000,
"rope_type": "default"
},
"sliding_window": null,
"tie_word_embeddings": false,
"transformers_version": "5.5.0",
"use_cache": false,
"use_sliding_window": false,
"vocab_size": 151936
}

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"top_k": 20,
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"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
"model_max_length": 131072,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null
}

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