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Improve language tag

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Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

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  1. README.md +177 -163
README.md CHANGED
@@ -1,164 +1,178 @@
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- ---
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- library_name: peft
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- license: apache-2.0
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- base_model: Qwen/Qwen2.5-1.5B
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- tags:
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- - axolotl
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- - generated_from_trainer
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- model-index:
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- - name: 02c6ef79-3237-4226-805b-3f9f629a401f
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- results: []
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- ---
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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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-
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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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-
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- axolotl version: `0.4.1`
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- ```yaml
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- adapter: lora
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- base_model: Qwen/Qwen2.5-1.5B
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- bf16: true
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- chat_template: llama3
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- dataset_prepared_path: null
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- datasets:
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- - data_files:
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- - c052ca56b26aee0f_train_data.json
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- ds_type: json
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- format: custom
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- path: /workspace/input_data/c052ca56b26aee0f_train_data.json
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- type:
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- field_instruction: title
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- field_output: description
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- format: '{instruction}'
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- no_input_format: '{instruction}'
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- system_format: '{system}'
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- system_prompt: ''
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- debug: null
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- deepspeed: null
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- device_map: auto
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- do_eval: true
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- early_stopping_patience: 5
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- eval_batch_size: 4
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- eval_max_new_tokens: 128
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- eval_steps: 50
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- eval_table_size: null
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- evals_per_epoch: null
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- flash_attention: true
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- fp16: false
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- fsdp: null
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- fsdp_config: null
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- gradient_accumulation_steps: 4
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- gradient_checkpointing: true
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- group_by_length: true
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- hub_model_id: alchemist69/02c6ef79-3237-4226-805b-3f9f629a401f
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- hub_repo: null
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- hub_strategy: checkpoint
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- hub_token: null
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- learning_rate: 0.0001
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- load_in_4bit: false
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- load_in_8bit: false
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- local_rank: null
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- logging_steps: 1
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- lora_alpha: 128
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- lora_dropout: 0.05
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- lora_fan_in_fan_out: null
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- lora_model_dir: null
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- lora_r: 64
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- lora_target_linear: true
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- lr_scheduler: cosine
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- max_grad_norm: 1.0
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- max_memory:
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- 0: 75GB
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- max_steps: 200
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- micro_batch_size: 8
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- mlflow_experiment_name: /tmp/c052ca56b26aee0f_train_data.json
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- model_type: AutoModelForCausalLM
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- num_epochs: 3
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- optim_args:
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- adam_beta1: 0.9
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- adam_beta2: 0.95
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- adam_epsilon: 1e-5
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- optimizer: adamw_bnb_8bit
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- output_dir: miner_id_24
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- pad_to_sequence_len: true
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- resume_from_checkpoint: null
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- s2_attention: null
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- sample_packing: false
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- save_steps: 50
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- saves_per_epoch: null
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- sequence_len: 1024
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- strict: false
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- tf32: true
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- tokenizer_type: AutoTokenizer
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- train_on_inputs: false
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- trust_remote_code: true
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- val_set_size: 0.05
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- wandb_entity: null
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- wandb_mode: online
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- wandb_name: 2a71d5a8-8bef-4bbd-aef1-2dc83ebcb262
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- wandb_project: Gradients-On-Demand
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- wandb_run: your_name
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- wandb_runid: 2a71d5a8-8bef-4bbd-aef1-2dc83ebcb262
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- warmup_steps: 10
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- weight_decay: 0.0
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- xformers_attention: null
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-
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- ```
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-
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- </details><br>
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-
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- # 02c6ef79-3237-4226-805b-3f9f629a401f
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-
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- This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B](https://huggingface.co/Qwen/Qwen2.5-1.5B) on the None dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 2.9580
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
126
-
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- ## Training and evaluation data
128
-
129
- More information needed
130
-
131
- ## Training procedure
132
-
133
- ### Training hyperparameters
134
-
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- The following hyperparameters were used during training:
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- - learning_rate: 0.0001
137
- - train_batch_size: 8
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- - eval_batch_size: 4
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- - seed: 42
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 32
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- - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
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- - lr_scheduler_type: cosine
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- - lr_scheduler_warmup_steps: 10
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- - training_steps: 200
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:------:|:----:|:---------------:|
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- | 2.8093 | 0.0001 | 1 | 3.1680 |
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- | 3.4058 | 0.0053 | 50 | 3.0492 |
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- | 3.6886 | 0.0106 | 100 | 2.9903 |
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- | 3.4669 | 0.0160 | 150 | 2.9625 |
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- | 3.3468 | 0.0213 | 200 | 2.9580 |
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-
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-
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- ### Framework versions
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-
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- - PEFT 0.13.2
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- - Transformers 4.46.0
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- - Pytorch 2.5.0+cu124
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- - Datasets 3.0.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - Tokenizers 0.20.1
 
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: Qwen/Qwen2.5-1.5B
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ language:
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+ - zho
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+ - eng
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+ - fra
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+ - spa
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+ - por
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+ - deu
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+ - ita
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+ - rus
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+ - jpn
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+ - kor
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+ - vie
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+ - tha
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+ - ara
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+ model-index:
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+ - name: 02c6ef79-3237-4226-805b-3f9f629a401f
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+ results: []
25
+ ---
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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
28
+ should probably proofread and complete it, then remove this comment. -->
29
+
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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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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ adapter: lora
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+ base_model: Qwen/Qwen2.5-1.5B
37
+ bf16: true
38
+ chat_template: llama3
39
+ dataset_prepared_path: null
40
+ datasets:
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+ - data_files:
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+ - c052ca56b26aee0f_train_data.json
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+ ds_type: json
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+ format: custom
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+ path: /workspace/input_data/c052ca56b26aee0f_train_data.json
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+ type:
47
+ field_instruction: title
48
+ field_output: description
49
+ format: '{instruction}'
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+ no_input_format: '{instruction}'
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+ system_format: '{system}'
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+ system_prompt: ''
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+ debug: null
54
+ deepspeed: null
55
+ device_map: auto
56
+ do_eval: true
57
+ early_stopping_patience: 5
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+ eval_batch_size: 4
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+ eval_max_new_tokens: 128
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+ eval_steps: 50
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+ eval_table_size: null
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+ evals_per_epoch: null
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+ flash_attention: true
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+ fp16: false
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+ fsdp: null
66
+ fsdp_config: null
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+ gradient_accumulation_steps: 4
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+ gradient_checkpointing: true
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+ group_by_length: true
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+ hub_model_id: alchemist69/02c6ef79-3237-4226-805b-3f9f629a401f
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+ hub_repo: null
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+ hub_strategy: checkpoint
73
+ hub_token: null
74
+ learning_rate: 0.0001
75
+ load_in_4bit: false
76
+ load_in_8bit: false
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+ local_rank: null
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+ logging_steps: 1
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+ lora_alpha: 128
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+ lora_dropout: 0.05
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+ lora_fan_in_fan_out: null
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+ lora_model_dir: null
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+ lora_r: 64
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+ lora_target_linear: true
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+ lr_scheduler: cosine
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+ max_grad_norm: 1.0
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+ max_memory:
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+ 0: 75GB
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+ max_steps: 200
90
+ micro_batch_size: 8
91
+ mlflow_experiment_name: /tmp/c052ca56b26aee0f_train_data.json
92
+ model_type: AutoModelForCausalLM
93
+ num_epochs: 3
94
+ optim_args:
95
+ adam_beta1: 0.9
96
+ adam_beta2: 0.95
97
+ adam_epsilon: 1e-5
98
+ optimizer: adamw_bnb_8bit
99
+ output_dir: miner_id_24
100
+ pad_to_sequence_len: true
101
+ resume_from_checkpoint: null
102
+ s2_attention: null
103
+ sample_packing: false
104
+ save_steps: 50
105
+ saves_per_epoch: null
106
+ sequence_len: 1024
107
+ strict: false
108
+ tf32: true
109
+ tokenizer_type: AutoTokenizer
110
+ train_on_inputs: false
111
+ trust_remote_code: true
112
+ val_set_size: 0.05
113
+ wandb_entity: null
114
+ wandb_mode: online
115
+ wandb_name: 2a71d5a8-8bef-4bbd-aef1-2dc83ebcb262
116
+ wandb_project: Gradients-On-Demand
117
+ wandb_run: your_name
118
+ wandb_runid: 2a71d5a8-8bef-4bbd-aef1-2dc83ebcb262
119
+ warmup_steps: 10
120
+ weight_decay: 0.0
121
+ xformers_attention: null
122
+
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+ ```
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+
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+ </details><br>
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+
127
+ # 02c6ef79-3237-4226-805b-3f9f629a401f
128
+
129
+ This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B](https://huggingface.co/Qwen/Qwen2.5-1.5B) on the None dataset.
130
+ It achieves the following results on the evaluation set:
131
+ - Loss: 2.9580
132
+
133
+ ## Model description
134
+
135
+ More information needed
136
+
137
+ ## Intended uses & limitations
138
+
139
+ More information needed
140
+
141
+ ## Training and evaluation data
142
+
143
+ More information needed
144
+
145
+ ## Training procedure
146
+
147
+ ### Training hyperparameters
148
+
149
+ The following hyperparameters were used during training:
150
+ - learning_rate: 0.0001
151
+ - train_batch_size: 8
152
+ - eval_batch_size: 4
153
+ - seed: 42
154
+ - gradient_accumulation_steps: 4
155
+ - total_train_batch_size: 32
156
+ - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
157
+ - lr_scheduler_type: cosine
158
+ - lr_scheduler_warmup_steps: 10
159
+ - training_steps: 200
160
+
161
+ ### Training results
162
+
163
+ | Training Loss | Epoch | Step | Validation Loss |
164
+ |:-------------:|:------:|:----:|:---------------:|
165
+ | 2.8093 | 0.0001 | 1 | 3.1680 |
166
+ | 3.4058 | 0.0053 | 50 | 3.0492 |
167
+ | 3.6886 | 0.0106 | 100 | 2.9903 |
168
+ | 3.4669 | 0.0160 | 150 | 2.9625 |
169
+ | 3.3468 | 0.0213 | 200 | 2.9580 |
170
+
171
+
172
+ ### Framework versions
173
+
174
+ - PEFT 0.13.2
175
+ - Transformers 4.46.0
176
+ - Pytorch 2.5.0+cu124
177
+ - Datasets 3.0.1
178
  - Tokenizers 0.20.1