Model save
Browse files- README.md +167 -0
- generation_config.json +14 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- axolotl
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- generated_from_trainer
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datasets:
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- train_rationale_unseen_whole_re.jsonl
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model-index:
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- name: merged-bench-0417-1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<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)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.8.0`
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```yaml
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base_model: Qwen/Qwen2.5-7B-Instruct
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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trust_remote_code: false
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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output_dir: ./outputs/out
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chat_template: qwen_25
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datasets:
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- path: train_rationale_unseen_whole_re.jsonl
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type: chat_template
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field_messages: messages
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message_field_role: role
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message_field_content: content
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roles:
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system:
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- system
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user:
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- user
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assistant:
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- assistant
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.005
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output_dir: ./outputs/out
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eval_sample_packing: False
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sequence_len: 8192
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sample_packing: False
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pad_to_sequence_len: False
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wandb_project: mergedbench
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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hub_model_id: amphora/merged-bench-0417-1
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_swiglu: true
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liger_fused_linear_cross_entropy: true
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gradient_accumulation_steps: 4
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micro_batch_size: 8
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eval_batch_size: 4
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num_epochs: 3
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 2e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 30
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evals_per_epoch: 3
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eval_max_new_tokens: 128
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed: deepspeed_configs/zero3_bf16.json
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weight_decay: 0.01
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fsdp:
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fsdp_config:
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special_tokens:
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```
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</details><br>
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# merged-bench-0417-1
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the train_rationale_unseen_whole_re.jsonl dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4004
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 16
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 30
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- num_epochs: 3.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.7481 | 0.0081 | 1 | 1.7361 |
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| 0.4091 | 0.3313 | 41 | 0.4241 |
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| 0.3857 | 0.6626 | 82 | 0.4033 |
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| 0.3516 | 0.9939 | 123 | 0.3825 |
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| 0.23 | 1.3313 | 164 | 0.3929 |
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| 0.2441 | 1.6626 | 205 | 0.3659 |
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| 0.2118 | 1.9939 | 246 | 0.3628 |
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| 0.1137 | 2.3313 | 287 | 0.4025 |
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| 0.1183 | 2.6626 | 328 | 0.4001 |
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| 0.1077 | 2.9939 | 369 | 0.4004 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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generation_config.json
ADDED
@@ -0,0 +1,14 @@
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{
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"bos_token_id": 151643,
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"pad_token_id": 151643,
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"repetition_penalty": 1.05,
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"temperature": 0.7,
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"top_k": 20,
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"top_p": 0.8,
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"transformers_version": "4.51.3"
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}
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