trillionlabs
/

android_control_ER_index_1000

@@ -1,208 +1,155 @@
 ---
-base_model: Qwen/Qwen3-8B
 library_name: peft
-pipeline_tag: text-generation
 tags:
 - axolotl
 - base_model:adapter:Qwen/Qwen3-8B
 - lora
 - transformers
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
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-## Uses
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-## How to Get Started with the Model
-Use the code below to get started with the model.
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-## Training Details
-### Training Data
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-### Training Procedure
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-#### Training Hyperparameters
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-## Evaluation
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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 ### Framework versions
-- PEFT 0.17.0

 ---
 library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen3-8B
 tags:
 - axolotl
 - base_model:adapter:Qwen/Qwen3-8B
 - lora
 - transformers
+datasets:
+- trillionlabs/android_control_ER_index_1000
+pipeline_tag: text-generation
+model-index:
+- name: android_control_ER_index_1000
+  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: `0.12.2`
+```yaml
+base_model: Qwen/Qwen3-8B
+strict: false
+chat_template: tokenizer_default
+datasets:
+  - path: trillionlabs/android_control_ER_index_1000
+    type: chat_template
+    split: train
+    field_messages: messages
+adapter: lora
+lora_model_dir:
+lora_r: 32
+lora_alpha: 64
+lora_dropout: 0.05
+lora_target_linear: true
+dataset_prepared_path: datasets/android_control_ER_index_1000_prepared
+val_set_size: 0.01
+output_dir: ./outputs/sft_android_control_ER_index_1000
+hub_model_id: trillionlabs/android_control_ER_index_1000
+sequence_len: 6144
+sample_packing: false
+pad_to_sequence_len: false
+wandb_project: axolotl
+wandb_entity: suyeong_korea_univ-korea-university
+wandb_name: android_control_ER_index_1000
+gradient_accumulation_steps: 2
+micro_batch_size: 2
+num_epochs: 2
+optimizer: adamw_torch_fused
+lr_scheduler: cosine
+learning_rate: 3e-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
+max_prompt_len: 6144
+warmup_steps: 50
+evals_per_epoch: 0
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+  - full_shard
+  - auto_wrap
+fsdp_config:
+  fsdp_limit_all_gathers: true
+  fsdp_sync_module_states: true
+  fsdp_offload_params: true
+  fsdp_use_orig_params: false
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_state_dict_type: FULL_STATE_DICT
+  fsdp_sharding_strategy: FULL_SHARD
+  fsdp_backward_prefetch: BACKWARD_PRE
+special_tokens:
+  pad_token: <|pad_token|>
+  eos_token: <|im_end|>
+seed: 11
+```
+</details><br>
+# android_control_ER_index_1000
+This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the trillionlabs/android_control_ER_index_1000 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: 3e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 11
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- total_eval_batch_size: 8
+- 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: 50
+- training_steps: 689
+### Training results
 ### Framework versions
+- PEFT 0.17.0
+- Transformers 4.56.0
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.0