End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- train_T2J.jsonl
+model-index:
+- name: FC-T2J-SFT-1_5B
+  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: `0.15.0.dev0`
+```yaml
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+
+load_in_8bit: false
+load_in_4bit: false
+
+datasets:
+  - path: train_T2J.jsonl
+    type: chat_template
+
+dataset_prepared_path: preprocess
+val_set_size: 0.01
+output_dir: ./outputs
+
+adapter: 
+lora_model_dir:
+
+sequence_len: 16384
+sample_packing: false
+eval_sample_packing: false
+pad_to_sequence_len: false
+
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_swiglu: true
+liger_fused_linear_cross_entropy: true
+
+wandb_project: FC-T2J
+wandb_entity: 
+wandb_watch:
+wandb_name: 
+wandb_log_model:
+hub_model_id: amphora/FC-T2J-SFT-1_5B
+
+gradient_accumulation_steps: 128
+micro_batch_size: 2
+num_epochs: 3
+optimizer: adamw_torch_fused
+lr_scheduler: cosine
+learning_rate: 2e-5
+
+bf16: auto
+tf32: false
+
+gradient_checkpointing:
+resume_from_checkpoint:
+logging_steps: 1
+flash_attention: true
+
+warmup_ratio: 0.05
+weight_decay: 0.01
+evals_per_epoch: 0
+saves_per_epoch: 1
+
+# fsdp_config:
+#   fsdp_version: 2
+#   fsdp_offload_params: false
+#   fsdp_cpu_ram_efficient_loading: true
+#   fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+#   fsdp_transformer_layer_cls_to_wrap: Qwen3DecoderLayer
+#   fsdp_state_dict_type: FULL_STATE_DICT
+#   fsdp_sharding_strategy: FULL_SHARD
+#   fsdp_reshard_after_forward: true
+#   fsdp_activation_checkpointing: true
+
+```
+
+</details><br>
+
+# FC-T2J-SFT-1_5B
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the train_T2J.jsonl 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: 2e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 128
+- total_train_batch_size: 256
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 87
+- training_steps: 1751
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.9.1+cu128
+- Datasets 4.5.0
+- Tokenizers 0.22.2