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Model: laion/Sera-4.6-Lite-T2-v4-316-axolotl__Qwen3-8B Source: Original Platform
2026-05-12 18:36:28 +08:00
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+---
+library_name: transformers
+base_model: Qwen/Qwen3-8B
+tags:
+- generated_from_trainer
+datasets:
+- laion/Sera-4.6-Lite-T2-v4-316
+model-index:
+- name: e/data1/datasets/playground/ot-baf/checkpoints/sera-v4-316-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
+# Sera v4 axolotl config template — consumes laion/Sera-4.6-Lite-T2-v4-<SIZE>
+# where tool_calls are already pre-rendered into content as <tool_call>...</tool_call>
+# (Hermes/Qwen3 wire format) per SERA's transform_traj_hermes. Chatml passes the
+# wire tokens through into input_ids + labels so tool calls are in the loss.
+#
+# 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
+
+# CCE disabled (aarch64/torch2.9 grad explosion — see baselines/sera/README.md)
+# plugins:
+#   - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
+
+chat_template: chatml
+datasets:
+  - path: laion/Sera-4.6-Lite-T2-v4-316
+    data_files:
+      - sera-4.6-lite-t2_v4_316.jsonl
+    type: chat_template
+    field_messages: messages
+    ds_type: json
+    message_field_training: train
+
+dataset_prepared_path: /e/data1/datasets/playground/ot-baf/axolotl_dataset_cache/sera-v4-316
+output_dir: /e/data1/datasets/playground/ot-baf/checkpoints/sera-v4-316-axolotl__Qwen3-8B
+
+sequence_len: 32768
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name: sera-v4-316-axolotl__Qwen3-8B
+wandb_log_model:
+
+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/sera-v4-316-axolotl__Qwen3-8B
+
+This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the laion/Sera-4.6-Lite-T2-v4-316 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: 3
+- training_steps: 17
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 5.5.0
+- Pytorch 2.9.1+cu130
+- Datasets 4.5.0
+- Tokenizers 0.22.2