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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 +160 -146
README.md CHANGED
@@ -1,147 +1,161 @@
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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: 82ada24c-76de-4c70-8839-2f84800960fe
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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: auto
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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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- - 949cd5eda3d6a876_train_data.json
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- ds_type: json
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- field: notes
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- path: /workspace/input_data/949cd5eda3d6a876_train_data.json
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- type: completion
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- debug: null
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- deepspeed: null
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- early_stopping_patience: 1
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- eval_max_new_tokens: 128
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- eval_steps: 25
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- eval_table_size: null
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- flash_attention: false
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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: 16
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- gradient_checkpointing: true
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- group_by_length: true
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- hub_model_id: DeepDream2045/82ada24c-76de-4c70-8839-2f84800960fe
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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: 64
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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: 32
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- lora_target_linear: true
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- lr_scheduler: cosine
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- max_steps: 50
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- micro_batch_size: 2
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- mlflow_experiment_name: /tmp/949cd5eda3d6a876_train_data.json
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- model_type: AutoModelForCausalLM
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- num_epochs: 3
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- optimizer: adamw_torch
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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: 25
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- sequence_len: 2048
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- strict: false
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- tf32: false
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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: 82ada24c-76de-4c70-8839-2f84800960fe
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- wandb_project: Gradients-On-Demand
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- wandb_run: your_name
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- wandb_runid: 82ada24c-76de-4c70-8839-2f84800960fe
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- warmup_ratio: 0.05
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- weight_decay: 0.01
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- xformers_attention: true
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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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- # 82ada24c-76de-4c70-8839-2f84800960fe
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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: 2.7513
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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
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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- - train_batch_size: 2
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- - eval_batch_size: 2
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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: 16
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- - total_train_batch_size: 128
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- - total_eval_batch_size: 8
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- - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 2
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- - training_steps: 50
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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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- | 2.884 | 0.0041 | 1 | 3.2208 |
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- | 2.636 | 0.1024 | 25 | 2.8128 |
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- | 2.5226 | 0.2049 | 50 | 2.7513 |
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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 2.4.1+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: 82ada24c-76de-4c70-8839-2f84800960fe
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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: auto
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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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+ - 949cd5eda3d6a876_train_data.json
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+ ds_type: json
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+ field: notes
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+ path: /workspace/input_data/949cd5eda3d6a876_train_data.json
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+ type: completion
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+ debug: null
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+ deepspeed: null
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+ early_stopping_patience: 1
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+ eval_max_new_tokens: 128
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+ eval_steps: 25
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+ eval_table_size: null
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+ flash_attention: false
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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: 16
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+ gradient_checkpointing: true
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+ group_by_length: true
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+ hub_model_id: DeepDream2045/82ada24c-76de-4c70-8839-2f84800960fe
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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: 64
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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: 32
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+ lora_target_linear: true
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+ lr_scheduler: cosine
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+ max_steps: 50
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+ micro_batch_size: 2
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+ mlflow_experiment_name: /tmp/949cd5eda3d6a876_train_data.json
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+ model_type: AutoModelForCausalLM
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+ num_epochs: 3
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+ optimizer: adamw_torch
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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: 25
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+ sequence_len: 2048
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+ strict: false
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+ tf32: false
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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: 82ada24c-76de-4c70-8839-2f84800960fe
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+ wandb_project: Gradients-On-Demand
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+ wandb_run: your_name
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+ wandb_runid: 82ada24c-76de-4c70-8839-2f84800960fe
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+ warmup_ratio: 0.05
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+ weight_decay: 0.01
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+ xformers_attention: true
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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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+ # 82ada24c-76de-4c70-8839-2f84800960fe
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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: 2.7513
114
+
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+ ## Model description
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+
117
+ More information needed
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+
119
+ ## Intended uses & limitations
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+
121
+ More information needed
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+
123
+ ## Training and evaluation data
124
+
125
+ More information needed
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+
127
+ ## Training procedure
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+
129
+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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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: 16
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 8
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 2
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+ - training_steps: 50
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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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+ | 2.884 | 0.0041 | 1 | 3.2208 |
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+ | 2.636 | 0.1024 | 25 | 2.8128 |
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+ | 2.5226 | 0.2049 | 50 | 2.7513 |
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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 2.4.1+cu124
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+ - Datasets 3.0.1
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  - Tokenizers 0.20.1